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Dynamic Documents with R and knitr

ISBN/GTIN

Dynamic Documents with R and knitr

by

BookPaperback

Ranking52218inInformatik EDV

CHF99.90

BookfromCHF99.90

E-bookfromCHF125.75

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Description

2nd edition.

More descriptions

Details

ISBN/GTIN978-1-4987-1696-3

Product TypeBook

BindingPaperback

PublisherTaylor and FrancisChapman and Hall/CRC

Publishing date22/06/2015

Edition2. A.

SeriesChapman & Hall/CRC The R Series

Pages294 pages

LanguageEnglish

SizeWidth 156 mm, Height 234 mm, Thickness 20 mm

Weight408 g

IllustrationsFarb., s/w. Abb.

Article no.22170053

CatalogsBuchzentrum

Data source no.18146262

Product groupInformatik EDV

Series

Dealing with Memory Limits and Working with Large Data Sets in R

Statistical Computing with R

R Graphics

Statistical Computing in C++ and R

Event History Analysis with R

Customer and Business Analytics

Programming Graphical User Interfaces in R

Analyzing Baseball Data with R

Implementing Reproducible Research

Stated Preference Methods Using R

Growth Curve Analysis and Visualization Using R

Computational Actuarial Science with R

Multiple Factor Analysis by Example Using R

Analyzing Sensory Data with R

Displaying Time Series, Spatial, and Space-Time Data with R

Using R for Numerical Analysis in Science and Engineering

Advanced R

Introduction to Scientific Programming and Simulation Using R

Using R for Introductory Statistics

Data Science in R

Parallel Computing for Data Science

Dynamic Documents with R and knitr

Statistics in Toxicology Using R

Graphical Data Analysis with R

Reproducible Research with R and R Studio

Introductory Fisheries Analyses with R

Using the R Commander

bookdown

Spatial Microsimulation with R

The Essentials of Data Science: Knowledge Discovery Using R

R Primer

Dynamic Documents with R and knitr

Reproducible Research with R and R Studio

Extending R

bookdown

Using the R Commander

Customer and Business Analytics

R Primer

blogdown

Flexible Regression and Smoothing

Data Science in R

R Markdown

Reproducible Finance with R

Practical R for Mass Communication and Journalism

Practical R for Mass Communication and Journalism

Displaying Time Series, Spatial, and Space-Time Data with R

Statistical Computing with R, Second Edition

Hands-On Machine Learning with R

Advanced R, Second Edition

Advanced R, Second Edition

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Reproducible Research with R and RStudio

Learn R

Learn R

Learning Microeconometrics with R

Geocomputation with R

Digital Media

Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Interactive Documents with R

Engineering Production-Grade Shiny Apps

Engineering Production-Grade Shiny Apps

Javascript for R

Javascript for R

Advanced R Solutions

Advanced R Solutions

Dose-Response Analysis Using R

Statistics in Toxicology Using R

Distributions for Modeling Location, Scale, and Shape

Event History Analysis with R

Outstanding User Interfaces with Shiny

Outstanding User Interfaces with Shiny

Rasch Measurement Theory Analysis in R

Rasch Measurement Theory Analysis in R

Spatial Sampling with R

A Criminologist's Guide to R

R for Political Data Science

ANOVA and Mixed Models

ANOVA and Mixed Models

Open Science with R

Spatial Data Science

Starting Quantitative Analysis with R

Analyzing US Census Data

Analyzing US Census Data

Deep Learning and Scientific Computing with R torch

Tidy Finance with R

Model-Based Clustering, Classification, and Density Estimation Using mclust in R

Graphical Data Analysis with R

Statistical Computing in C++ and R

Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Modern Data Visualization with R

Modern Data Visualization with R

Learn R

Learn R

Behavior Analysis with Machine Learning Using R

Event History Analysis with R

Spatial Analysis in Geology Using R

Analyzing Baseball Data with R

Analyzing Baseball Data with R

Introductory Fisheries Analyses with R

Multiple Factor Analysis by Example Using R

Author

Yihui Xie is a software engineer at RStudio. He earned a PhD from the Department of Statistics at Iowa State University. His research focuses on interactive statistical graphics and statistical computing. He is an active R user and the author of several award-winning R packages, such as animation, formatR, Rd2roxygen, and knitr. He is also the founder of "Capital of Statistics," a large online statistics community in China.