Advanced R Statistical Programming and Data Models

Analysis, Machine Learning, and Visualization

Autor: Matt Wiley, Joshua F. Wiley

Język:

Oprawa: Miękka

Wydawca: APress

Dostępność: Dostępna u dostawcy

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Carry out a variety of advanced statistical analyses including generalized additive models, mixed ef...

Informacje o książce

Autor

Matt Wiley, Joshua F. Wiley

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2019

strony

638

EAN

9781484228715

ISBN

1484228715

Enbook ID

17438493

Wydawca

APress

Waga

1246

Wymiary

258 x 184 x 42

Pełny opis

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and concludes with a case study. Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data analysis using the popular R language. You'll delve into the preconditions or hypothesis for various statistical tests and techniques and work through concrete examples using R for a variety of these next-level analytics. This is a must-have guide and reference on using and programming with the R language. What You'll Learn Conduct advanced analyses in R including: generalized linear models, generalized additive models, mixed effects models, machine learning, and parallel processing Carry out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R including parallel processing, dimension reduction, and feature selection and classification Address missing data using multiple imputation in R Work on factor analysis, generalized linear mixed models, and modeling intraindividual variability Who This Book Is For Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. Particularly, researchers and data analysts in the social sciences may benefit from these techniques. Additionally, analysts who need parallel processing to speed up analytics are given proven code to reduce time to result(s).

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Analysis, Machine Learning, and Visualization

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