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2.4 FIGURES
A guide to authoring books with R Markdown, including how to generate figures and tables, and insert cross-references, citations, HTML widgets, and Shiny apps in R Markdown. The book can be exported to HTML, PDF, and e-books (e.g. EPUB). The book style is customizable. You can easily write and preview the book in RStudio IDE or other editors, and host the book wherever you want (e.g. bookdown CHAPTER 5 THE FIRST LAW FOR OPEN SYSTEMS The First Law for open systems. An open system allows mass flows across the system boundary. Mass flow rate is measured in . Many of the systems engineers work with, are open systems. The jet engine of an aircraft is an open system. The turbines, boilers and pumps in large-scale power generation plants are open systems. 16.4 CHILD DOCUMENTS (*) 16.4 Child documents (*). When you feel an R Markdown document is too long, you may consider splitting it into shorter documents, and include them as child documents of the main document via the chunk option child.The child option takes a character vector of paths to the child documents, e.g., 9.2 THE RMDFORMATS PACKAGE 9.2 The rmdformats package. The rmdformats package (Barnier 2021) provides several HTML output formats of unique and attractive styles, including:. material: A format based on the Material design theme for Bootstrap 3.With this format, every first-level section will become a separate page. See Figure 9.2 for what this format looks like (“Introduction” and “Including Plots” are two CHAPTER 11 CHUNK OPTIONS This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other 2 TMAP | MAKING MAPS WITH R 2.2 Static maps with tmap. Most often, geographical data are displayed using static maps that can be saved as .png or .pdf files. Originally, data could only be visualized in this way in R, but the development of new packages, especially sp, has created new possibilities for displaying this data.Despite new methods like interactive maps, static maps are still the main focus of geospatial data CHAPTER 13 BAYESIAN META-ANALYSIS Chapter 13 Bayesian Meta-Analysis. After delving into rather advanced extensions of Meta-Analysis, such as Network Meta-Analysis and Multilevel Meta-Analysis, let us now take one step back and look at “conventional” meta-analytical models again, but this time from another angle.In this chapter, we will deal with Bayesian Meta-Analysis.In its essence, Bayesian Meta-Analysis aims to do the 10.1 THE FUNCTION KNITR::KABLE() 10.1. The function. knitr::kable () The kable () function in knitr is a very simple table generator, and is simple by design. It only generates tables for strictly rectangular data such as matrices and data frames. You cannot heavily format the table cells or merge cells. However, this function does have a large number of arguments for youto
HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and BLOGDOWN: CREATING WEBSITES WITH R MARKDOWNCREATING WEBSITES WITH R MARKDOWNABOUT THE AUTHORS1 GET STARTED2 HUGO3 DEPLOYMENT Preface. In the summer of 2012, I did my internship at AT&T Labs Research, 1 where I attended a talk given by Carlos Scheidegger (https://cscheid.net), and Carlos said something along the lines of “if you don’t have a website nowadays, you don’t exist.”Later I paraphrased it as: “I web, therefore I am a spiderman.”. Carlos’s words resonated very well with me, although they were a2.4 FIGURES
A guide to authoring books with R Markdown, including how to generate figures and tables, and insert cross-references, citations, HTML widgets, and Shiny apps in R Markdown. The book can be exported to HTML, PDF, and e-books (e.g. EPUB). The book style is customizable. You can easily write and preview the book in RStudio IDE or other editors, and host the book wherever you want (e.g. bookdown CHAPTER 5 THE FIRST LAW FOR OPEN SYSTEMS The First Law for open systems. An open system allows mass flows across the system boundary. Mass flow rate is measured in . Many of the systems engineers work with, are open systems. The jet engine of an aircraft is an open system. The turbines, boilers and pumps in large-scale power generation plants are open systems. 16.4 CHILD DOCUMENTS (*) 16.4 Child documents (*). When you feel an R Markdown document is too long, you may consider splitting it into shorter documents, and include them as child documents of the main document via the chunk option child.The child option takes a character vector of paths to the child documents, e.g., 9.2 THE RMDFORMATS PACKAGE 9.2 The rmdformats package. The rmdformats package (Barnier 2021) provides several HTML output formats of unique and attractive styles, including:. material: A format based on the Material design theme for Bootstrap 3.With this format, every first-level section will become a separate page. See Figure 9.2 for what this format looks like (“Introduction” and “Including Plots” are two CHAPTER 11 CHUNK OPTIONS This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other 2 TMAP | MAKING MAPS WITH R 2.2 Static maps with tmap. Most often, geographical data are displayed using static maps that can be saved as .png or .pdf files. Originally, data could only be visualized in this way in R, but the development of new packages, especially sp, has created new possibilities for displaying this data.Despite new methods like interactive maps, static maps are still the main focus of geospatial data CHAPTER 13 BAYESIAN META-ANALYSIS Chapter 13 Bayesian Meta-Analysis. After delving into rather advanced extensions of Meta-Analysis, such as Network Meta-Analysis and Multilevel Meta-Analysis, let us now take one step back and look at “conventional” meta-analytical models again, but this time from another angle.In this chapter, we will deal with Bayesian Meta-Analysis.In its essence, Bayesian Meta-Analysis aims to do the 10.1 THE FUNCTION KNITR::KABLE() 10.1. The function. knitr::kable () The kable () function in knitr is a very simple table generator, and is simple by design. It only generates tables for strictly rectangular data such as matrices and data frames. You cannot heavily format the table cells or merge cells. However, this function does have a large number of arguments for youto
HOME | BOOKDOWN
The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and 5.8 MULTI-COLUMN LAYOUT (*) 5.8 Multi-column layout (*) 5.8. Multi-column layout (*) Pandoc’s Markdown supports the multi-column layout for slides but not other types of documents. In this recipe, we show how to use the multi-column layout in normal HTML documents and LaTeX documents. This recipe was inspired by Atsushi Yasumoto’s solutions to the knitrissue https
B QUICK START
B.2 Estimating \(\beta\) of a Stock. To estimate the “beta” (\(\beta\)) of a stock:Load the quantmod package.; Use the getSymbols() function to pull the historical returns data for a particular stock over a given period.; Use getSymbols() to pull the S&P 500 market returns data for the same time period.; Extract the returns from the objects created in steps 2 & 3. 4.8 UPDATE THE DATE AUTOMATICALLY 4.8 Update the date automatically. If you want the date on which the Rmd document is compiled to be reflected in the output report, you can add an inline R expression to the date field in YAML, and use the Sys.Date() or Sys.time() function to obtain the current date, e.g., A DEVELOPMENT ENVIRONMENTS A.1 Local RStudio. RStudio is a free, open-source software environment that you can install on your computer to write and run R code. The standard version of RStudio is a desktop application, which means that it runs locally on your machine and not in the cloud. 7.14 LAYERS: THE BUILDING BLOCKS OF DEEP LEARNING Deep-learning model: directed, acyclic graph of layers Most common is a linear stack of layers, mapping a single input to a single output; Layer: a data-processing module that takes as input one or more tensors and that outputs one or more tensors. Different layer types for different tensor formats/data processing types (e.g., densely connected layers, recurrent layers etc.) DATA SCIENCE BOOT CAMP 1.1.1 Core texts and resources. R4DS: R for Data Science by Hadley Wickham and Garrett Grolemund. An excellent introduction, available for free online. Boot Camp Notes: Data Science Boot Camp by Arthur Small. These notes. DataCamp.Online interactive courseware 7.2 CLASSICAL ML: WHAT IT DOES (1) What’s a representation? A different way to look at data (to represent or encode data); e.g., color image encoded in RGB format (red-green-blue) or in the HSV format (hue-saturation-value): these are two different representations of the same data; Some (classification) tasks that may be difficult with one representation can become easy with another (e.g, “select all red pixels in theimage
SESSION 7 MACHINE LEARNING: INTRO TO DEEP LEARNING Chollet, Francois, and J J Allaire. 2018. Deep Learning with R. 1st ed. Manning Publications.. 1st ed. Manning Publications. 7.18 LAB: PREDICTING HOUSE PRICES: A REGRESSION EXAMPLE 7.18.0.5 Confronting the model with test data. Generally, we would tune our model in different ways, e.g., in addition to the number of epochs we could adjust the size of the hidden layers etc. (maybe also include different variables) HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The platform bookdown.org is provided by RStudio for authors to publish books online for free. The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. 5.8 MULTI-COLUMN LAYOUT (*) The CSS attribute display: inline-block; means the output code blocks (i.e., the tags in HTML) should be displayed as inline elements. By default, these blocks are displayed as block-level elements (i.e., display: block;) and will occupy whole rows.The chunk option collapse = TRUE means the text output will be merged into the R source code block, so both the source and its text output 4.9 MULTIPLE AUTHORS IN A DOCUMENT This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other CHAPTER 5 THE DIAMONDS DATASET Chapter 5 The diamonds dataset. Throughout this chapter, we will be working with the diamonds dataset, so let’s take a minute to familiarize ourselves with it. This built-in dataset is available when the ggplot2 package is loaded. Loading the tidyverse package will automatically load ggplot2.. Let’s view the diamonds dataset in a separate RStudio tab:. View (diamonds) 2 TMAP | MAKING MAPS WITH R 2.2 Static maps with tmap. Most often, geographical data are displayed using static maps that can be saved as .png or .pdf files. Originally, data could only be visualized in this way in R, but the development of new packages, especially sp, has created new possibilities for displaying this data.Despite new methods like interactive maps, static maps are still the main focus of geospatial data 5.4 CONTROL THE SIZE OF PLOTS/IMAGES 5.4 Control the size of plots/images. The size of plots made in R can be controlled by the chunk option fig.width and fig.height (in inches). Equivalently, you can use the fig.dim option to specify the width and height in a numeric vector of length 2, e.g., fig.dim = c(8, 6) means fig.width = 8 and fig.height = 6.These options set the physical size of plots, and you can choose to display a CHAPTER 5 THE FIRST LAW FOR OPEN SYSTEMS 5.1.4 Compressed liquids and solids. Because of the small value of \(v\) for liquids and solids, the \(Pv\) term Equation is much smaller than \(u\).As the internal energy of solids and liquids changes very little with pressure anyway, the change in enthalpy with pressure is also small and it can be assumed that the enthalpy of a compressed liquid (and solid) is the same as that of a saturated R FOR EVERYONE (ADVANCED ANALYTICS AND GRAPHICS) AND LATEX This is an introduction to R and Latex. In compiling this documents, several sources have been consulted, including Jared P. Lander's R for Everyone, Hadley Wickham and Garrett Grolemund's R for Data Science, Dr. Yuleng Zeng's website, Dr. Timothy M. Peterson’s website, Havard’s Math Prefresher, the course offered by DataCamp.Chapter 3 and Chapter 4 are mostly borrowed from Dr. Yuleng Zeng PRINCIPLES OF ECONOMETRICS WITH R 1.2. HOW TO OPEN A DATA FILE 11 1.1.1 TheScript,ordata view window HereareafewtipsforwritingandexecutingscriptintheScriptwindow DATA VISUALIZATION WITH GGPLOT2 : : CHEAT SHEET Scales Coordinate Systems. A stat builds new variables to plot (e.g., count, prop). Stats . An alternative way to build a layer + = datageom . x = x ·
HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The platform bookdown.org is provided by RStudio for authors to publish books online for free. The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. 5.8 MULTI-COLUMN LAYOUT (*) The CSS attribute display: inline-block; means the output code blocks (i.e., the tags in HTML) should be displayed as inline elements. By default, these blocks are displayed as block-level elements (i.e., display: block;) and will occupy whole rows.The chunk option collapse = TRUE means the text output will be merged into the R source code block, so both the source and its text output 4.9 MULTIPLE AUTHORS IN A DOCUMENT This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other CHAPTER 5 THE DIAMONDS DATASET Chapter 5 The diamonds dataset. Throughout this chapter, we will be working with the diamonds dataset, so let’s take a minute to familiarize ourselves with it. This built-in dataset is available when the ggplot2 package is loaded. Loading the tidyverse package will automatically load ggplot2.. Let’s view the diamonds dataset in a separate RStudio tab:. View (diamonds) 2 TMAP | MAKING MAPS WITH R 2.2 Static maps with tmap. Most often, geographical data are displayed using static maps that can be saved as .png or .pdf files. Originally, data could only be visualized in this way in R, but the development of new packages, especially sp, has created new possibilities for displaying this data.Despite new methods like interactive maps, static maps are still the main focus of geospatial data 5.4 CONTROL THE SIZE OF PLOTS/IMAGES 5.4 Control the size of plots/images. The size of plots made in R can be controlled by the chunk option fig.width and fig.height (in inches). Equivalently, you can use the fig.dim option to specify the width and height in a numeric vector of length 2, e.g., fig.dim = c(8, 6) means fig.width = 8 and fig.height = 6.These options set the physical size of plots, and you can choose to display a CHAPTER 5 THE FIRST LAW FOR OPEN SYSTEMS 5.1.4 Compressed liquids and solids. Because of the small value of \(v\) for liquids and solids, the \(Pv\) term Equation is much smaller than \(u\).As the internal energy of solids and liquids changes very little with pressure anyway, the change in enthalpy with pressure is also small and it can be assumed that the enthalpy of a compressed liquid (and solid) is the same as that of a saturated R FOR EVERYONE (ADVANCED ANALYTICS AND GRAPHICS) AND LATEX This is an introduction to R and Latex. In compiling this documents, several sources have been consulted, including Jared P. Lander's R for Everyone, Hadley Wickham and Garrett Grolemund's R for Data Science, Dr. Yuleng Zeng's website, Dr. Timothy M. Peterson’s website, Havard’s Math Prefresher, the course offered by DataCamp.Chapter 3 and Chapter 4 are mostly borrowed from Dr. Yuleng Zeng PRINCIPLES OF ECONOMETRICS WITH R 1.2. HOW TO OPEN A DATA FILE 11 1.1.1 TheScript,ordata view window HereareafewtipsforwritingandexecutingscriptintheScriptwindow DATA VISUALIZATION WITH GGPLOT2 : : CHEAT SHEET Scales Coordinate Systems. A stat builds new variables to plot (e.g., count, prop). Stats . An alternative way to build a layer + = datageom . x = x ·
5.8 MULTI-COLUMN LAYOUT (*) The CSS attribute display: inline-block; means the output code blocks (i.e., the tags in HTML) should be displayed as inline elements. By default, these blocks are displayed as block-level elements (i.e., display: block;) and will occupy whole rows.The chunk option collapse = TRUE means the text output will be merged into the R source code block, so both the source and its text outputB QUICK START
B.2 Estimating \(\beta\) of a Stock. To estimate the “beta” (\(\beta\)) of a stock:Load the quantmod package.; Use the getSymbols() function to pull the historical returns data for a particular stock over a given period.; Use getSymbols() to pull the S&P 500 market returns data for the same time period.; Extract the returns from the objects created in steps 2 & 3. 8.2 THE TWO-WAY WORKFLOW BETWEEN R MARKDOWN AND WORD This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other 1.2 INSTALL LATEX (TINYTEX) FOR PDF REPORTS 1.2 Install LaTeX (TinyTeX) for PDF reports. If you would like to create PDF documents from R Markdown, you will need to have a LaTeX distribution installed. Although there are several traditional options including MiKTeX, MacTeX, and TeX Live, we recommend that R Markdown users install TinyTeX.. TinyTeX is a custom LaTeX distribution based on TeX Live that is relatively small in size, but A DEVELOPMENT ENVIRONMENTS A.1 Local RStudio. RStudio is a free, open-source software environment that you can install on your computer to write and run R code. The standard version of RStudio is a desktop application, which means that it runs locally on your machine and not in the cloud. 7.7 UNDERSTANDING HOW DL WORKS (1) Specification of what a layer does to its input data is stored in the layer’s weights (= a bunch of numbers) (see See Figure 7.4) . Weights are also sometimes called the parameters of a layer 7.14 LAYERS: THE BUILDING BLOCKS OF DEEP LEARNING Deep-learning model: directed, acyclic graph of layers Most common is a linear stack of layers, mapping a single input to a single output; Layer: a data-processing module that takes as input one or more tensors and that outputs one or more tensors. Different layer types for different tensor formats/data processing types (e.g., densely connected layers, recurrent layers etc.) DATA SCIENCE BOOT CAMP 1.1.1 Core texts and resources. R4DS: R for Data Science by Hadley Wickham and Garrett Grolemund. An excellent introduction, available for free online. Boot Camp Notes: Data Science Boot Camp by Arthur Small. These notes. DataCamp.Online interactive courseware 7.2 CLASSICAL ML: WHAT IT DOES (1) What’s a representation? A different way to look at data (to represent or encode data); e.g., color image encoded in RGB format (red-green-blue) or in the HSV format (hue-saturation-value): these are two different representations of the same data; Some (classification) tasks that may be difficult with one representation can become easy with another (e.g, “select all red pixels in theimage
7.18 LAB: PREDICTING HOUSE PRICES: A REGRESSION EXAMPLE 7.18.0.5 Confronting the model with test data. Generally, we would tune our model in different ways, e.g., in addition to the number of epochs we could adjust the size of the hidden layers etc. (maybe also include different variables) HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and 9.6 CUSTOM BLOCKS (*) 9.6.1 Syntax. The syntax for custom blocks is based on Pandoc’s fenced Div blocks. Div blocks are very powerful, but there is a problem at the moment: they mainly work for HTML output and do not work for LaTeX output.. Since version 1.16 of the rmarkdown package, it has been possible to convert Div blocks to both HTML and LaTeX. For HTML output, all attributes of the block will become 4.24 ASSUMPTIONS: SUTVA 4.24. Assumptions: SUTVA. SUTVA: Stable Unit Treatment Values Assumption. -1- No interference & -2- No hidden variations of treatment. The potential outcomes for any unit do not vary with the treatments assigned to other units. A subject’s potential outcome isnot
4.9 MULTIPLE AUTHORS IN A DOCUMENT 4.9. Multiple authors in a document. We can add multiple authors to an R Markdown document within the YAML frontmatter in a number of ways. If we simply want to list them on the same line, we can provide a single string to the document, e.g., --- title: "Untitled" author: "John Doe, Jane Doe" ---. Alternatively, if we wish each entry to beon
9.2 THE RMDFORMATS PACKAGE 9.2 The rmdformats package. The rmdformats package (Barnier 2021) provides several HTML output formats of unique and attractive styles, including:. material: A format based on the Material design theme for Bootstrap 3.With this format, every first-level section will become a separate page. See Figure 9.2 for what this format looks like (“Introduction” and “Including Plots” are two CHAPTER 13 BAYESIAN META-ANALYSIS Chapter 13 Bayesian Meta-Analysis. After delving into rather advanced extensions of Meta-Analysis, such as Network Meta-Analysis and Multilevel Meta-Analysis, let us now take one step back and look at “conventional” meta-analytical models again, but this time from another angle.In this chapter, we will deal with Bayesian Meta-Analysis.In its essence, Bayesian Meta-Analysis aims to do the CHAPTER 11 CHUNK OPTIONS This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other 10.1 THE FUNCTION KNITR::KABLE() 10.1. The function. knitr::kable () The kable () function in knitr is a very simple table generator, and is simple by design. It only generates tables for strictly rectangular data such as matrices and data frames. You cannot heavily format the table cells or merge cells. However, this function does have a large number of arguments for youto
DOING BAYESIAN DATA ANALYSIS IN BRMS AND THE TIDYVERSE Kruschke began his text with “This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours).”. In the same way, this project is designed to help those real people do Bayesian data analysis. My contribution is converting Kruschke’s JAGS and Stan code for use in Bürkner’sbrms
6 EXPLORATORY GRAPHS 6.2 Air Pollution in the United States. For this chapter, we will use a simple case study to demonstrate the kinds of simple graphs that can be useful in exploratory analyses. The data we will be using come from the U.S. Environmental Protection Agency (EPA), which is the U.S. government agency that sets national air quality standards for outdoorair pollution.
HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and 9.6 CUSTOM BLOCKS (*) 9.6.1 Syntax. The syntax for custom blocks is based on Pandoc’s fenced Div blocks. Div blocks are very powerful, but there is a problem at the moment: they mainly work for HTML output and do not work for LaTeX output.. Since version 1.16 of the rmarkdown package, it has been possible to convert Div blocks to both HTML and LaTeX. For HTML output, all attributes of the block will become 4.24 ASSUMPTIONS: SUTVA 4.24. Assumptions: SUTVA. SUTVA: Stable Unit Treatment Values Assumption. -1- No interference & -2- No hidden variations of treatment. The potential outcomes for any unit do not vary with the treatments assigned to other units. A subject’s potential outcome isnot
4.9 MULTIPLE AUTHORS IN A DOCUMENT 4.9. Multiple authors in a document. We can add multiple authors to an R Markdown document within the YAML frontmatter in a number of ways. If we simply want to list them on the same line, we can provide a single string to the document, e.g., --- title: "Untitled" author: "John Doe, Jane Doe" ---. Alternatively, if we wish each entry to beon
9.2 THE RMDFORMATS PACKAGE 9.2 The rmdformats package. The rmdformats package (Barnier 2021) provides several HTML output formats of unique and attractive styles, including:. material: A format based on the Material design theme for Bootstrap 3.With this format, every first-level section will become a separate page. See Figure 9.2 for what this format looks like (“Introduction” and “Including Plots” are two CHAPTER 13 BAYESIAN META-ANALYSIS Chapter 13 Bayesian Meta-Analysis. After delving into rather advanced extensions of Meta-Analysis, such as Network Meta-Analysis and Multilevel Meta-Analysis, let us now take one step back and look at “conventional” meta-analytical models again, but this time from another angle.In this chapter, we will deal with Bayesian Meta-Analysis.In its essence, Bayesian Meta-Analysis aims to do the CHAPTER 11 CHUNK OPTIONS This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other 10.1 THE FUNCTION KNITR::KABLE() 10.1. The function. knitr::kable () The kable () function in knitr is a very simple table generator, and is simple by design. It only generates tables for strictly rectangular data such as matrices and data frames. You cannot heavily format the table cells or merge cells. However, this function does have a large number of arguments for youto
DOING BAYESIAN DATA ANALYSIS IN BRMS AND THE TIDYVERSE Kruschke began his text with “This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours).”. In the same way, this project is designed to help those real people do Bayesian data analysis. My contribution is converting Kruschke’s JAGS and Stan code for use in Bürkner’sbrms
6 EXPLORATORY GRAPHS 6.2 Air Pollution in the United States. For this chapter, we will use a simple case study to demonstrate the kinds of simple graphs that can be useful in exploratory analyses. The data we will be using come from the U.S. Environmental Protection Agency (EPA), which is the U.S. government agency that sets national air quality standards for outdoorair pollution.
2.4 FIGURES
A guide to authoring books with R Markdown, including how to generate figures and tables, and insert cross-references, citations, HTML widgets, and Shiny apps in R Markdown. The book can be exported to HTML, PDF, and e-books (e.g. EPUB). The book style is customizable. You can easily write and preview the book in RStudio IDE or other editors, and host the book wherever you want (e.g. bookdown 4.5 BIBLIOGRAPHIES AND CITATIONS 4.5 Bibliographies and citations. 4.5. Bibliographies and citations. For an overview of including bibliographies in your output document, you may see Section 2.8 of Xie ( 2016). The basic usage requires us to specify a bibliography file using the bibliography metadata field in YAML. For example: where the BibTeX database is a plain-text file 6.4 INCLUDE ADDITIONAL LATEX PACKAGES 6.4 Include additional LaTeX packages. The use of additional LaTeX packages can allow for extensive customization of document styling. In addition, several packages such as kableExtra may have LaTeX dependencies for the R package to function. Much like R, we need to load packages within the R Markdown document before we are able to usetheir functions.
3.4 CONVERT R MARKDOWN TO R SCRIPT 3.4 Convert R Markdown to R script. When you want to extract all R code from an R Markdown document, you can call the function knitr::purl().Below is a simple Rmd example with the filename purl.Rmd:---title: Use `purl()` to extract R code---The function `knitr::purl()` extracts R code chunks from a **knitr** document and save the code to an R script.CHAPTER 8 R LAB 7
8.2 Linear regression model with step functions. We consider now the case of a linear regression model with step functions defined by the classes of lstat_ord.In this case a constant model will be estimated for each of the 4 regions. We don’t have to do anything special in this case apart from specifying a standard linear model where lstat_ord is the only regressor. 7.1 ARTIFICIAL, MACHINE AND DEEP LEARNING Artificial intelligence: The effort to automate intellectual tasks normally performed by humans (Chollet’s concise definition, field born in 1950s, Symbolic AI → Machine learning) DATA SCIENCE BOOT CAMP 1.1.1 Core texts and resources. R4DS: R for Data Science by Hadley Wickham and Garrett Grolemund. An excellent introduction, available for free online. Boot Camp Notes: Data Science Boot Camp by Arthur Small. These notes. DataCamp.Online interactive courseware8.2 EXAMPLE
Acharya, Avidit, Matthew Blackwell, and Maya Sen. 2016. “Explaining Causal Findings Without Bias: Detecting and Assessing Direct Effects.” Am. Polit. Sci. Rev 7.14 LAYERS: THE BUILDING BLOCKS OF DEEP LEARNING Deep-learning model: directed, acyclic graph of layers Most common is a linear stack of layers, mapping a single input to a single output; Layer: a data-processing module that takes as input one or more tensors and that outputs one or more tensors. Different layer types for different tensor formats/data processing types (e.g., densely connected layers, recurrent layers etc.)PHI4-ANALYSIS
This book contain the result of the analysis of the phi4 scatteringproject
HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and 5.8 MULTI-COLUMN LAYOUT (*) 5.8 Multi-column layout (*) 5.8. Multi-column layout (*) Pandoc’s Markdown supports the multi-column layout for slides but not other types of documents. In this recipe, we show how to use the multi-column layout in normal HTML documents and LaTeX documents. This recipe was inspired by Atsushi Yasumoto’s solutions to the knitrissue https
5.4 CONTROL THE SIZE OF PLOTS/IMAGES 5.4 Control the size of plots/images. The size of plots made in R can be controlled by the chunk option fig.width and fig.height (in inches). Equivalently, you can use the fig.dim option to specify the width and height in a numeric vector of length 2, e.g., fig.dim = c(8, 6) means fig.width = 8 and fig.height = 6.These options set the physical size of plots, and you can choose to display a 4.8 UPDATE THE DATE AUTOMATICALLY 4.5.1 Changing citation style. 4.5.2 Add an item to a bibliography without using it. 4.5.3 Add all items to the bibliography. 4.5.4 Include appendix after bibliography (*) 4.6 Generate R package citations. 4.7 Cross-referencing within documents. 4.8 Update the date automatically. 4.9 Multiple authors in a document. 1.2 INSTALL LATEX (TINYTEX) FOR PDF REPORTS 1.2 Install LaTeX (TinyTeX) for PDF reports. If you would like to create PDF documents from R Markdown, you will need to have a LaTeX distribution installed. Although there are several traditional options including MiKTeX, MacTeX, and TeX Live, we recommend that R Markdown users install TinyTeX.. TinyTeX is a custom LaTeX distribution based on TeX Live that is relatively small in size, but CHAPTER 5 THE DIAMONDS DATASET Chapter 5 The diamonds dataset. Throughout this chapter, we will be working with the diamonds dataset, so let’s take a minute to familiarize ourselves with it. This built-in dataset is available when the ggplot2 package is loaded. Loading the tidyverse package will automatically load ggplot2.. Let’s view the diamonds dataset in a separate RStudio tab:. View (diamonds) ESNA II | THE TEMPLE OF ESNA. AN EVOLVING TRANSLATION: ESNA II As a first goal, I am working exclusively on the Roman Period inscriptions from Esna II (scenes 46-193). So far, 148/148 (100%) of those scenes are complete and online. I started with the shortest inscriptions, and am now slowly working through the 4.24 ASSUMPTIONS: SUTVA 4.24. Assumptions: SUTVA. SUTVA: Stable Unit Treatment Values Assumption. -1- No interference & -2- No hidden variations of treatment. The potential outcomes for any unit do not vary with the treatments assigned to other units. A subject’s potential outcome isnot
DOING BAYESIAN DATA ANALYSIS IN BRMS AND THE TIDYVERSE Kruschke began his text with “This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours).”. In the same way, this project is designed to help those real people do Bayesian data analysis. My contribution is converting Kruschke’s JAGS and Stan code for use in Bürkner’sbrms
CHAPTER 8 CROSS-TABULATION Chapter 8 Cross-Tabulation. Chapter 8. Cross-Tabulation. This chapter provides generic code for generating a contingency table and carrying out a chi-square test of independence. It is recommended that you proceed through the sections in the order they appear. Placeholders that need replacing: HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and 5.8 MULTI-COLUMN LAYOUT (*) 5.8 Multi-column layout (*) 5.8. Multi-column layout (*) Pandoc’s Markdown supports the multi-column layout for slides but not other types of documents. In this recipe, we show how to use the multi-column layout in normal HTML documents and LaTeX documents. This recipe was inspired by Atsushi Yasumoto’s solutions to the knitrissue https
5.4 CONTROL THE SIZE OF PLOTS/IMAGES 5.4 Control the size of plots/images. The size of plots made in R can be controlled by the chunk option fig.width and fig.height (in inches). Equivalently, you can use the fig.dim option to specify the width and height in a numeric vector of length 2, e.g., fig.dim = c(8, 6) means fig.width = 8 and fig.height = 6.These options set the physical size of plots, and you can choose to display a 4.8 UPDATE THE DATE AUTOMATICALLY 4.5.1 Changing citation style. 4.5.2 Add an item to a bibliography without using it. 4.5.3 Add all items to the bibliography. 4.5.4 Include appendix after bibliography (*) 4.6 Generate R package citations. 4.7 Cross-referencing within documents. 4.8 Update the date automatically. 4.9 Multiple authors in a document. 1.2 INSTALL LATEX (TINYTEX) FOR PDF REPORTS 1.2 Install LaTeX (TinyTeX) for PDF reports. If you would like to create PDF documents from R Markdown, you will need to have a LaTeX distribution installed. Although there are several traditional options including MiKTeX, MacTeX, and TeX Live, we recommend that R Markdown users install TinyTeX.. TinyTeX is a custom LaTeX distribution based on TeX Live that is relatively small in size, but CHAPTER 5 THE DIAMONDS DATASET Chapter 5 The diamonds dataset. Throughout this chapter, we will be working with the diamonds dataset, so let’s take a minute to familiarize ourselves with it. This built-in dataset is available when the ggplot2 package is loaded. Loading the tidyverse package will automatically load ggplot2.. Let’s view the diamonds dataset in a separate RStudio tab:. View (diamonds) ESNA II | THE TEMPLE OF ESNA. AN EVOLVING TRANSLATION: ESNA II As a first goal, I am working exclusively on the Roman Period inscriptions from Esna II (scenes 46-193). So far, 148/148 (100%) of those scenes are complete and online. I started with the shortest inscriptions, and am now slowly working through the 4.24 ASSUMPTIONS: SUTVA 4.24. Assumptions: SUTVA. SUTVA: Stable Unit Treatment Values Assumption. -1- No interference & -2- No hidden variations of treatment. The potential outcomes for any unit do not vary with the treatments assigned to other units. A subject’s potential outcome isnot
DOING BAYESIAN DATA ANALYSIS IN BRMS AND THE TIDYVERSE Kruschke began his text with “This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours).”. In the same way, this project is designed to help those real people do Bayesian data analysis. My contribution is converting Kruschke’s JAGS and Stan code for use in Bürkner’sbrms
CHAPTER 8 CROSS-TABULATION Chapter 8 Cross-Tabulation. Chapter 8. Cross-Tabulation. This chapter provides generic code for generating a contingency table and carrying out a chi-square test of independence. It is recommended that you proceed through the sections in the order they appear. Placeholders that need replacing: 16.4 CHILD DOCUMENTS (*) 16.4 Child documents (*). When you feel an R Markdown document is too long, you may consider splitting it into shorter documents, and include them as child documents of the main document via the chunk option child.The child option takes a character vector of paths to the child documents, e.g.,R MARKDOWN COOKBOOK
R Markdown is a powerful tool for combining analysis and reporting into the same document. Since the birth of the rmarkdown package (Allaire, Xie, McPherson, et al. 2021) in early 2014, R Markdown has grown substantially from a package that supports a few output formats, to an extensive and diverse ecosystem that supports the creation of books, blogs, scientific articles, websites, and 6.4 INCLUDE ADDITIONAL LATEX PACKAGES 6.4 Include additional LaTeX packages. The use of additional LaTeX packages can allow for extensive customization of document styling. In addition, several packages such as kableExtra may have LaTeX dependencies for the R package to function. Much like R, we need to load packages within the R Markdown document before we are able to usetheir functions.
CHAPTER 2 MACHINE LEARNING TOOLS 2.1 K-Nearest Neighbors (KNN). kNN is a simple and very useful method, in which predictions are made taking into account the values of the closest instances of the new COVID-19 number ofCHAPTER 8 R LAB 7
8.2 Linear regression model with step functions. We consider now the case of a linear regression model with step functions defined by the classes of lstat_ord.In this case a constant model will be estimated for each of the 4 regions. We don’t have to do anything special in this case apart from specifying a standard linear model where lstat_ord is the only regressor. 7.14 LAYERS: THE BUILDING BLOCKS OF DEEP LEARNING Deep-learning model: directed, acyclic graph of layers Most common is a linear stack of layers, mapping a single input to a single output; Layer: a data-processing module that takes as input one or more tensors and that outputs one or more tensors. Different layer types for different tensor formats/data processing types (e.g., densely connected layers, recurrent layers etc.)8.2 EXAMPLE
Acharya, Avidit, Matthew Blackwell, and Maya Sen. 2016. “Explaining Causal Findings Without Bias: Detecting and Assessing Direct Effects.” Am. Polit. Sci. Rev 7.8 UNDERSTANDING HOW DL WORKS (2) Figure 7.5: A loss function measures the quality of the network’s output (Chollet & Allaire, 2018, Fig. 1.8) 7.2 CLASSICAL ML: WHAT IT DOES (1) What’s a representation? A different way to look at data (to represent or encode data); e.g., color image encoded in RGB format (red-green-blue) or in the HSV format (hue-saturation-value): these are two different representations of the same data; Some (classification) tasks that may be difficult with one representation can become easy with another (e.g, “select all red pixels in theimage
7.18 LAB: PREDICTING HOUSE PRICES: A REGRESSION EXAMPLE 7.18.0.5 Confronting the model with test data. Generally, we would tune our model in different ways, e.g., in addition to the number of epochs we could adjust the size of the hidden layers etc. (maybe also include different variables) HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and 5.8 MULTI-COLUMN LAYOUT (*) 5.8 Multi-column layout (*) 5.8. Multi-column layout (*) Pandoc’s Markdown supports the multi-column layout for slides but not other types of documents. In this recipe, we show how to use the multi-column layout in normal HTML documents and LaTeX documents. This recipe was inspired by Atsushi Yasumoto’s solutions to the knitrissue https
5.4 CONTROL THE SIZE OF PLOTS/IMAGES 5.4 Control the size of plots/images. The size of plots made in R can be controlled by the chunk option fig.width and fig.height (in inches). Equivalently, you can use the fig.dim option to specify the width and height in a numeric vector of length 2, e.g., fig.dim = c(8, 6) means fig.width = 8 and fig.height = 6.These options set the physical size of plots, and you can choose to display a 4.8 UPDATE THE DATE AUTOMATICALLY 4.5.1 Changing citation style. 4.5.2 Add an item to a bibliography without using it. 4.5.3 Add all items to the bibliography. 4.5.4 Include appendix after bibliography (*) 4.6 Generate R package citations. 4.7 Cross-referencing within documents. 4.8 Update the date automatically. 4.9 Multiple authors in a document. 1.2 INSTALL LATEX (TINYTEX) FOR PDF REPORTS 1.2 Install LaTeX (TinyTeX) for PDF reports. If you would like to create PDF documents from R Markdown, you will need to have a LaTeX distribution installed. Although there are several traditional options including MiKTeX, MacTeX, and TeX Live, we recommend that R Markdown users install TinyTeX.. TinyTeX is a custom LaTeX distribution based on TeX Live that is relatively small in size, but CHAPTER 5 THE DIAMONDS DATASET Chapter 5 The diamonds dataset. Throughout this chapter, we will be working with the diamonds dataset, so let’s take a minute to familiarize ourselves with it. This built-in dataset is available when the ggplot2 package is loaded. Loading the tidyverse package will automatically load ggplot2.. Let’s view the diamonds dataset in a separate RStudio tab:. View (diamonds) ESNA II | THE TEMPLE OF ESNA. AN EVOLVING TRANSLATION: ESNA II As a first goal, I am working exclusively on the Roman Period inscriptions from Esna II (scenes 46-193). So far, 148/148 (100%) of those scenes are complete and online. I started with the shortest inscriptions, and am now slowly working through the 4.24 ASSUMPTIONS: SUTVA 4.24. Assumptions: SUTVA. SUTVA: Stable Unit Treatment Values Assumption. -1- No interference & -2- No hidden variations of treatment. The potential outcomes for any unit do not vary with the treatments assigned to other units. A subject’s potential outcome isnot
DOING BAYESIAN DATA ANALYSIS IN BRMS AND THE TIDYVERSE Kruschke began his text with “This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours).”. In the same way, this project is designed to help those real people do Bayesian data analysis. My contribution is converting Kruschke’s JAGS and Stan code for use in Bürkner’sbrms
CHAPTER 8 CROSS-TABULATION Chapter 8 Cross-Tabulation. Chapter 8. Cross-Tabulation. This chapter provides generic code for generating a contingency table and carrying out a chi-square test of independence. It is recommended that you proceed through the sections in the order they appear. Placeholders that need replacing: HOME | BOOKDOWNDOCUMENTATIONLOG INAN APPROACH TO IDENTIFY THE SOURCES OF LOW-CARBON GROWTH FOR EUROPE The bookdown package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: Generate printer-ready books and ebooks from R Markdown documents. A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, and 5.8 MULTI-COLUMN LAYOUT (*) 5.8 Multi-column layout (*) 5.8. Multi-column layout (*) Pandoc’s Markdown supports the multi-column layout for slides but not other types of documents. In this recipe, we show how to use the multi-column layout in normal HTML documents and LaTeX documents. This recipe was inspired by Atsushi Yasumoto’s solutions to the knitrissue https
5.4 CONTROL THE SIZE OF PLOTS/IMAGES 5.4 Control the size of plots/images. The size of plots made in R can be controlled by the chunk option fig.width and fig.height (in inches). Equivalently, you can use the fig.dim option to specify the width and height in a numeric vector of length 2, e.g., fig.dim = c(8, 6) means fig.width = 8 and fig.height = 6.These options set the physical size of plots, and you can choose to display a 4.8 UPDATE THE DATE AUTOMATICALLY 4.5.1 Changing citation style. 4.5.2 Add an item to a bibliography without using it. 4.5.3 Add all items to the bibliography. 4.5.4 Include appendix after bibliography (*) 4.6 Generate R package citations. 4.7 Cross-referencing within documents. 4.8 Update the date automatically. 4.9 Multiple authors in a document. 1.2 INSTALL LATEX (TINYTEX) FOR PDF REPORTS 1.2 Install LaTeX (TinyTeX) for PDF reports. If you would like to create PDF documents from R Markdown, you will need to have a LaTeX distribution installed. Although there are several traditional options including MiKTeX, MacTeX, and TeX Live, we recommend that R Markdown users install TinyTeX.. TinyTeX is a custom LaTeX distribution based on TeX Live that is relatively small in size, but CHAPTER 5 THE DIAMONDS DATASET Chapter 5 The diamonds dataset. Throughout this chapter, we will be working with the diamonds dataset, so let’s take a minute to familiarize ourselves with it. This built-in dataset is available when the ggplot2 package is loaded. Loading the tidyverse package will automatically load ggplot2.. Let’s view the diamonds dataset in a separate RStudio tab:. View (diamonds) ESNA II | THE TEMPLE OF ESNA. AN EVOLVING TRANSLATION: ESNA II As a first goal, I am working exclusively on the Roman Period inscriptions from Esna II (scenes 46-193). So far, 148/148 (100%) of those scenes are complete and online. I started with the shortest inscriptions, and am now slowly working through the 4.24 ASSUMPTIONS: SUTVA 4.24. Assumptions: SUTVA. SUTVA: Stable Unit Treatment Values Assumption. -1- No interference & -2- No hidden variations of treatment. The potential outcomes for any unit do not vary with the treatments assigned to other units. A subject’s potential outcome isnot
DOING BAYESIAN DATA ANALYSIS IN BRMS AND THE TIDYVERSE Kruschke began his text with “This book explains how to actually do Bayesian data analysis, by real people (like you), for realistic data (like yours).”. In the same way, this project is designed to help those real people do Bayesian data analysis. My contribution is converting Kruschke’s JAGS and Stan code for use in Bürkner’sbrms
CHAPTER 8 CROSS-TABULATION Chapter 8 Cross-Tabulation. Chapter 8. Cross-Tabulation. This chapter provides generic code for generating a contingency table and carrying out a chi-square test of independence. It is recommended that you proceed through the sections in the order they appear. Placeholders that need replacing:R MARKDOWN COOKBOOK
R Markdown is a powerful tool for combining analysis and reporting into the same document. Since the birth of the rmarkdown package (Allaire, Xie, McPherson, et al. 2021) in early 2014, R Markdown has grown substantially from a package that supports a few output formats, to an extensive and diverse ecosystem that supports the creation of books, blogs, scientific articles, websites, and 16.4 CHILD DOCUMENTS (*) 16.4 Child documents (*). When you feel an R Markdown document is too long, you may consider splitting it into shorter documents, and include them as child documents of the main document via the chunk option child.The child option takes a character vector of paths to the child documents, e.g., 6.4 INCLUDE ADDITIONAL LATEX PACKAGES 6.4 Include additional LaTeX packages. The use of additional LaTeX packages can allow for extensive customization of document styling. In addition, several packages such as kableExtra may have LaTeX dependencies for the R package to function. Much like R, we need to load packages within the R Markdown document before we are able to usetheir functions.
4.9 MULTIPLE AUTHORS IN A DOCUMENT 4.9. Multiple authors in a document. We can add multiple authors to an R Markdown document within the YAML frontmatter in a number of ways. If we simply want to list them on the same line, we can provide a single string to the document, e.g., --- title: "Untitled" author: "John Doe, Jane Doe" ---. Alternatively, if we wish each entry to beon
CHAPTER 8 R LAB 7
8.2 Linear regression model with step functions. We consider now the case of a linear regression model with step functions defined by the classes of lstat_ord.In this case a constant model will be estimated for each of the 4 regions. We don’t have to do anything special in this case apart from specifying a standard linear model where lstat_ord is the only regressor. 7.14 LAYERS: THE BUILDING BLOCKS OF DEEP LEARNING Deep-learning model: directed, acyclic graph of layers Most common is a linear stack of layers, mapping a single input to a single output; Layer: a data-processing module that takes as input one or more tensors and that outputs one or more tensors. Different layer types for different tensor formats/data processing types (e.g., densely connected layers, recurrent layers etc.)8.2 EXAMPLE
Acharya, Avidit, Matthew Blackwell, and Maya Sen. 2016. “Explaining Causal Findings Without Bias: Detecting and Assessing Direct Effects.” Am. Polit. Sci. Rev 8.1 ML APIS: AN OVERVIEW Script for the seminar ‘Big Data and Social Science’ at theUniversity of Bern.
7.2 CLASSICAL ML: WHAT IT DOES (1) What’s a representation? A different way to look at data (to represent or encode data); e.g., color image encoded in RGB format (red-green-blue) or in the HSV format (hue-saturation-value): these are two different representations of the same data; Some (classification) tasks that may be difficult with one representation can become easy with another (e.g, “select all red pixels in theimage
7.11 SHORT-TERM HYPE & PROMISE OF AI (CH. 1.1.7, 1.1.8 Chollet and Allaire (): Some world-changing applications within reach but many more likely to remain elusive for a long time e.g., autonomous cars vs. believable dialogue systems, human-level machine translation across arbitrary languages, and human-level natural-language understanding*
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BOOKDOWN
WRITE HTML, PDF, EPUB, AND KINDLE BOOKS WITH R MARKDOWN The BOOKDOWN package is an open-source R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: * Generate printer-ready books and ebooks from R Markdown documents. * A markup language easier to learn than LaTeX, and to write elements such as section headers, lists, quotes, figures, tables, andcitations.
* Multiple choices of output formats: PDF, LaTeX, HTML, EPUB, andWord.
* Possibility of including dynamic graphics and interactive applications (HTML widgets and Shiny apps). * Support a wide range of languages: R, C/C++, Python, Fortran, Julia, Shell scripts, and SQL, etc. * LaTeX equations, theorems, and proofs work for all output formats. * Can be published to GitHub, bookdown.org, and any web servers. * Integrated with the RStudio IDE. * One-click publishing to https://bookdown.org. Below is a list of featured books. For a full list, please see the archive page. For the full documentation of the BOOKDOWN package, please see the free online book _bookdown: Authoring Books and Technical Documents with R Markdown_.R MARKDOWN COOKBOOK
BY YIHUI XIE, CHRISTOPHE DERVIEUX, EMILY RIEDERER2021-06-02
This book showcases short, practical examples of lesser-known tips and tricks to helps users get the most out of these tools. After reading this book, you will understand how R Markdown documents are transformed from plain text and how you may customize nearly every step of this processing. For example, you will learn how to dynamically create content from R code, reference code in other documents or chunks, control the formatting with customer templates, fine-tune how your code is processed, and incorporate multiple languages into your analysis. Read more →1
R GRAPHICS COOKBOOK, 2ND EDITIONBY WINSTON CHANG
2021-06-02
This cookbook contains more than 150 recipes to help scientists, engineers, programmers, and data analysts generate high-quality graphs quickly—without having to comb through all the details of R’s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project and includes a discussion of how and why the recipe works. Welcome to the R Graphics Cookbook, a practical guide that provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R’s graphing systems. Each recipe …Read more →
2
BOOKDOWN: AUTHORING BOOKS AND TECHNICAL DOCUMENTS WITH R MARKDOWNBY YIHUI XIE
2021-05-25
A guide to authoring books with R Markdown, including how to generate figures and tables, and insert cross-references, citations, HTML widgets, and Shiny apps in R Markdown. The book can be exported to HTML, PDF, and e-books (e.g. EPUB). The book style is customizable. You can easily write and preview the book in RStudio IDE or other editors, and host the book wherever you want (e.g. bookdown.org).Read more →
3
INTRODUCTION TO DATA SCIENCE BY RAFAEL A. IRIZARRY2021-05-24
This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning and helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with GitHub, and reproducible document preparation with R markdown. Read more →4
BLOGDOWN: CREATING WEBSITES WITH R MARKDOWN BY YIHUI XIE, AMBER THOMAS, ALISON PRESMANES HILL2021-05-04
A guide to creating websites with R Markdown and the R package blogdown. A note from the authors: Some of the information and instructions in this book are now out of date because of changes to Hugo and the blogdown package. If you have suggestions for improving this book, please file an issue in our GitHub repository. Thanks for your patience while we work to update the book, and please stay tuned for the revised version! In the meantime, you can find an introduction to the changes and new features in the v1.0 release blog post and this “Up & running with blogdown in 2021” blog post. … Read more →5
R MARKDOWN: THE DEFINITIVE GUIDE BY YIHUI XIE, J. J. ALLAIRE, GARRETT GROLEMUND2021-04-09
The first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages. Read more →6
GEOCOMPUTATION WITH R BY ROBIN LOVELACE, JAKUB NOWOSAD, JANNES MUENCHOW2021-04-06
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. Read more →7
TEXT MINING WITH R
BY JULIA SILGE AND DAVID ROBINSON2021-04-06
This is the website for Text Mining with R! Visit the GitHub repository for this site, find the book at O’Reilly, or buy it on Amazon. This work by Julia Silge and David Robinson is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States … Read more →8
ENGINEERING PRODUCTION-GRADE SHINY APPS BY COLIN FAY, SÉBASTIEN ROCHETTE, VINCENT GUYADER, CERVAN GIRARD2021-04-02
A book about engineering shiny application that will later be sent to production. This book cover project management, structuring your project, building a solid testing suite, and optimizing your codebase. We describe in this book a specific workflow: design, prototype, build, strengthen and deploy. This book will soon be available in print, published in the R Series by Chapman & Hall. This book will not get you started with {shiny}, nor talk how to work with {shiny} once it is sent to production. What we will be discussing in this book is the process of building an application that … Read more →9
EFFICIENT R PROGRAMMING BY COLIN GILLESPIE, ROBIN LOVELACE2021-03-18
Efficient R Programming is about increasing the amount of work you can do with R in a given amount of time. It’s about both computational and programmer efficiency. This is the online version of the O’Reilly book: Efficient R programming. Pull requests and general comments are welcome. Get a hard copy from: Amazon (UK), Amazon (USA), O’Reilly Colin Gillespie is Senior Lecturer (Associate Professor) at Newcastle University, UK. He is an Executive Editor of the R Journal, with research interests including high performance statistical computing and Bayesian statistics. Colin founded the … Read more →10
STATISTICAL INFERENCE VIA DATA SCIENCE BY CHESTER ISMAY AND ALBERT Y. KIM2021-02-05
An open-source and fully-reproducible electronic textbook for teaching statistical inference using tidyverse data science tools. This is the website for Statistical Inference via Data Science: A ModernDive into R and the Tidyverse! Visit the GitHub repository for this site and find the book on Amazon. You can also purchase it at CRC Press using promo code ADC21 for a discounted price. This work by Chester Ismay and Albert Y. Kim is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International … Read more→
11
BEYOND MULTIPLE LINEAR REGRESSION BY PAUL ROBACK AND JULIE LEGLER2021-01-26
An applied textbook on generalized linear models and multilevel models for advanced undergraduates, featuring many real, unique data sets. It is intended to be accessible to undergraduate students who have successfully completed a regression course. Even though there is no mathematical prerequisite, we still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. We believe strongly in case studies featuring real data and real research questions; thus, most of the data in the textbook arises from collaborative research conducted by the authors and their students, or from student projects. Our goal is that, after working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling.Read more →
12
DATA SCIENCE AT THE COMMAND LINE, 1EBY JEROEN JANSSENS
2020-12-21
This is the website for Data Science at the Command Line, published by O’Reilly October 2014 First Edition. This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data. To get you started—whether you’re on Windows, macOS, or Linux—author Jeroen Janssens has developed a Docker image packed with over 80 command-line tools. Discover why the command line is an agile, scalable, and extensible … Read more →13
R PROGRAMMING FOR DATA SCIENCEBY ROGER D. PENG
2020-09-03
The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox. Read more →14
ADVANCED R
BY HADLEY WICKHAM
2021-06-03*
This is the website for 2nd edition of “Advanced R”, a book in Chapman & Hall’s R Series. The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as help you to understand why R works the way it does. If you’re looking for the 1st edition, you can find it at http://adv-r.had.co.nz/. This work, as a whole, is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The code contained in this book is simultaneously … Read more →15
DATA SCIENCE LIVE BOOKBY PABLO CASAS
2021-06-03*
An intuitive and practical approach to data analysis, data preparation and machine learning, suitable for all ages! This book is now available at Amazon. Check it out! 📗 🚀. Link to the black & white version, also available on full-color. It can be shipped to over 100 countries. 🌎 The book will facilitate the understanding of common issues when data analysis and machine learning are done. Building a predictive model is as difficult as one line of R code: That’s it. But, data has its dirtiness in practice. We need to sculp it, just like an artist does, to expose its information in order …Read more →
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DATA VISUALIZATION
BY KIERAN HEALY
2021-06-03*
A practical introduction. Published by Princeton University Press. Incomplete draft. This version: 2018-04-25. You should look at your data. Graphs and charts let you explore and learn about the structure of the information you collect. Good data visualizations also make it easier to communicate your ideas and findings to other people. Beyond that, producing effective plots from your own data is the best way to develop a good eye for reading and understanding graphs—good and bad—made by others, whether presented in research articles, business slide decks, public policy advocacy, or … Readmore →
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FORECASTING: PRINCIPLES AND PRACTICE (2ND ED) BY ROB J HYNDMAN AND GEORGE ATHANASOPOULOS2021-06-03*
This is the second edition of Forecasting: Principles & Practice, which uses the forecast package in R. The third edition, which uses the fable package, is also available. Welcome to our online textbook on forecasting. This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details. The book is … Read more→
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FUNDAMENTALS OF DATA VISUALIZATIONBY CLAUS O. WILKE
2021-06-03*
A guide to making visualizations that accurately reflect the data, tell a story, and look professional. This is the website for the book “Fundamentals of Data Visualization,” published by O’Reilly Media, Inc. The website contains the complete author manuscript before final copy-editing and other quality control. If you would like to order an official hardcopy or ebook, you can do so at various resellers, including Amazon, Barnes and Noble, Google Play, or Powells. The book is meant as a guide to making visualizations that accurately reflect the data, tell a story, and look professional. …Read more →
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HANDS-ON PROGRAMMING WITH R BY GARRETT GROLEMUND2021-06-03*
This book will teach you how to program in R, with hands-on examples. I wrote it for non-programmers to provide a friendly introduction to the R language. You’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools. Throughout the book, you’ll use your newfound skills to solve practical data science problems. Read more →20
R FOR DATA SCIENCE
BY HADLEY WICKHAM AND GARRETT GROLEMUND2021-06-03*
This is the website for “R for Data Science”. This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use … Read more→
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R PACKAGES
BY HADLEY WICKHAM, JENNIFER BRYAN2021-06-03*
Welcome to R packages by Hadley Wickham and Jenny Bryan. Packages are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data. In this book you’ll learn how to turn your code into packages that others can easily download and use. Writing a package can seem overwhelming at first. So start with the basics and improve it over time. It doesn’t matter if your first version isn’t perfect as long as the next version is better. This is the work-in-progress 2nd edition of the … Read more →22
RStudio, PBC 2016 – 2020Details
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