Dynamic Documents With R

Dynamic Documents with R and knitr (repost)  eBooks & eLearning

Posted by nebulae at May 25, 2017
Dynamic Documents with R and knitr (repost)

Yihui Xie, "Dynamic Documents with R and knitr"
2013 | ISBN-10: 1482203537 | 216 pages | PDF | 3 MB

Dynamic Documents with R and knitr (2nd Edition) (Repost)  eBooks & eLearning

Posted by insetes at Sept. 18, 2015
Dynamic Documents with R and knitr (2nd Edition) (Repost)

Dynamic Documents with R and knitr (2nd Edition) By Yihui Xie
2015 | 294 Pages | ISBN: 1498716962 | PDF | 6 MB

Dynamic Documents with R and knitr, Second Edition  eBooks & eLearning

Posted by AlenMiler at June 26, 2015
Dynamic Documents with R and knitr, Second Edition

Dynamic Documents with R and knitr, Second Edition (Chapman & Hall/CRC: The R Series) by Yihui Xie
English | 10 Aug. 2015 | ISBN: 1498716962 | 294 Pages | AZW4/PDF (True) | 14 MB

Suitable for both beginners and advanced users, Dynamic Documents with R and knitr, Second Edition makes writing statistical reports easier by integrating computing directly with reporting.

Dynamic Documents with R and knitr  eBooks & eLearning

Posted by arundhati at Oct. 11, 2014
Dynamic Documents with R and knitr

Yihui Xie, "Dynamic Documents with R and knitr"
2013 | ISBN-10: 1482203537 | 216 pages | PDF | 3 MB

bookdown: Authoring Books and Technical Documents with R Markdown  eBooks & eLearning

Posted by Underaglassmoon at Jan. 8, 2017
bookdown: Authoring Books and Technical Documents with R Markdown

bookdown: Authoring Books and Technical Documents with R Markdown
CRC Press | English | December 19, 2016 | ISBN-10: 113870010X | 138 pages | PDF | 1.69 mb

by Yihui Xie (Author)
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 citations

Bayesian Essentials with R (Springer Texts in Statistics)  eBooks & eLearning

Posted by hill0 at Jan. 19, 2018
Bayesian Essentials with R (Springer Texts in Statistics)

Bayesian Essentials with R (Springer Texts in Statistics) by Jean-Michel Marin
English | 29 Oct. 2013 | ISBN: 1461486866 | 312 Pages | EPUB | 5.34 MB

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package

Data Visualisation with R: 100 Examples [Repost]  eBooks & eLearning

Posted by hill0 at Jan. 17, 2018
Data Visualisation with R: 100 Examples [Repost]

Data Visualisation with R: 100 Examples by Thomas Rahlf
English | 20 Feb. 2017 | ISBN: 3319497502 | 404 Pages | PDF (True) | 99 MB

This book introduces readers to the fundamentals of creating presentation graphics using R, based on 100 detailed and complete scripts. It shows how bar and column charts, population pyramids, Lorenz curves, box plots,

Beginning Time Series Analysis and Forecasting with R  eBooks & eLearning

Posted by naag at Jan. 10, 2018
Beginning Time Series Analysis and Forecasting with R

Beginning Time Series Analysis and Forecasting with R
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours | 323 MB
Genre: eLearning | Language: English

Time series data is found in any field. This course will teach you how to handle this specific type of data and how to create forecasting models.

Data Manipulation with R and SQL  eBooks & eLearning

Posted by naag at Jan. 6, 2018
Data Manipulation with R and SQL

Data Manipulation with R and SQL
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 46M | 384 MB
Genre: eLearning | Language: English

Modern Optimization with R  eBooks & eLearning

Posted by AvaxGenius at Jan. 4, 2018
Modern Optimization with R

Modern Optimization with R By Paulo Cortez
English | EPUB | 2014 | 188 Pages | ISBN : 3319082620 | 1.47 MB

The goal of this book is to gather in a single document the most relevant concepts related to modern optimization methods, showing how such concepts and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristics, are particularly useful for solving complex problems for which no specialized optimization algorithm has been developed.