Multiple Comparisons Using R

Multiple Comparisons Using R (repost)  eBooks & eLearning

Posted by interes at June 30, 2014
Multiple Comparisons Using R (repost)

Multiple Comparisons Using R by Frank Bretz, Torsten Hothorn and Peter Westfall
English | 2010 | ISBN: 1584885742 | 202 pages | PDF | 4 MB

Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R.

Multiple Comparisons Using R (repost)  eBooks & eLearning

Posted by arundhati at Sept. 22, 2013
Multiple Comparisons Using R (repost)

Frank Bretz, Torsten Hothorn, "Multiple Comparisons Using R"
2010 | ISBN: 1584885742 | 202 pages | PDF | 4,1 MB

Multiple Comparisons Using R (Repost)  eBooks & eLearning

Posted by Specialselection at March 23, 2012
Multiple Comparisons Using R (Repost)

Frank Bretz, Torsten Hothorn, Peter Westfall, "Multiple Comparisons Using R"
English | 2010-07-27 | ISBN: 1584885742 | 202 pages | PDF | 2.9 mb

Machine Learning Using R  eBooks & eLearning

Posted by hill0 at Jan. 20, 2017
Machine Learning Using R

Machine Learning Using R by Karthik Ramasubramanian
English | 10 Jan. 2017 | ISBN: 1484223330 | 592 Pages | PDF | 11.47 MB

This book is inspired by the Machine Learning Model Building Process Flow, which provides the reader the ability to understand a ML algorithm and apply the entire process of building a ML model from the raw data.

Bioinformatics and Computational Biology Solutions Using R and Bioconductor [Repost]  eBooks & eLearning

Posted by tanas.olesya at Jan. 19, 2017
Bioinformatics and Computational Biology Solutions Using R and Bioconductor [Repost]

Bioinformatics and Computational Biology Solutions Using R and Bioconductor by Robert Gentleman
English | 31 Aug. 2005 | ISBN: 0387251464 | 496 Pages | PDF | 17 MB

Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies.

Applied Biclustering Methods for Big and High-Dimensional Data Using R  eBooks & eLearning

Posted by ksveta6 at Jan. 13, 2017
Applied Biclustering Methods for Big and High-Dimensional Data Using R

Applied Biclustering Methods for Big and High-Dimensional Data Using R (Chapman & Hall/CRC Biostatistics Series) by Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
2016 | ISBN: 1482208237 | English | 433 pages | PDF | 17 MB

Molecular Data Analysis Using R  eBooks & eLearning

Posted by Underaglassmoon at Jan. 9, 2017
Molecular Data Analysis Using R

Molecular Data Analysis Using R
Wiley-Blackwell | English | January 2017 | ISBN-10: 1119165024 | 352 pages | PDF | 7.54 mb

By Csaba Ortutay, Zsuzsanna Ortutay

Social Network Analysis Using R  eBooks & eLearning

Posted by naag at Jan. 5, 2017
Social Network Analysis Using R

Social Network Analysis Using R
MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 1 Hours | 133 MB
Genre: eLearning | Language: English

Using R for Digital Soil Mapping (Progress in Soil Science)  eBooks & eLearning

Posted by hill0 at Dec. 24, 2016
Using R for Digital Soil Mapping (Progress in Soil Science)

Using R for Digital Soil Mapping (Progress in Soil Science) by Brendan P. Malone
English | 25 Nov. 2016 | ISBN: 3319443259 | 262 Pages | PDF | 5.13 MB

This book describes and provides many detailed examples of implementing Digital Soil Mapping (DSM) using R. The work adheres to Digital Soil Mapping theory, and presents a strong focus on how to apply it. DSM exercises are also included and cover procedures for handling and manipulating soil and spatial data in R.

Multilevel Modeling Using R  eBooks & eLearning

Posted by tanas.olesya at Dec. 23, 2016
Multilevel Modeling Using R

Multilevel Modeling Using R by W. Holmes Finch
English | 30 July 2014 | ISBN: 1466515856 | 230 Pages | PDF | 3 MB

A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modeling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software environment.