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  3. Matematik til informatikfag

Advanced R Statistical Programming and Data Models

- Analysis, Machine Learning, and Visualization
Af: Joshua F. Wiley, Matt Wiley Engelsk Paperback

Advanced R Statistical Programming and Data Models

- Analysis, Machine Learning, and Visualization
Af: Joshua F. Wiley, Matt Wiley Engelsk Paperback
Tjek vores konkurrenters priser
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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Tjek vores konkurrenters priser
Normalpris
kr 669
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser
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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Se mere i:
Produktdetaljer
Sprog: Engelsk
Sider: 638
ISBN-13: 9781484228715
Indbinding: Paperback
Udgave:
ISBN-10: 1484228715
Kategori: Matematik til informatikfag
Udg. Dato: 21 feb 2019
Længde: 42mm
Bredde: 258mm
Højde: 184mm
Forlag: APress
Oplagsdato: 21 feb 2019
Forfatter(e): Joshua F. Wiley, Matt Wiley
Forfatter(e) Joshua F. Wiley, Matt Wiley

Kategori Matematik til informatikfag

ISBN-13 9781484228715

Sprog Engelsk

Indbinding Paperback

Sider 638

Udgave

Længde 42mm

Bredde 258mm

Højde 184mm

Udg. Dato 21 feb 2019

Oplagsdato 21 feb 2019

Forlag APress

Kategori sammenhænge