Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization

Author:   Matt Wiley ,  Joshua F. Wiley
Publisher:   APress
Edition:   1st ed.
ISBN:  

9781484228715


Pages:   638
Publication Date:   21 February 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization


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Author:   Matt Wiley ,  Joshua F. Wiley
Publisher:   APress
Imprint:   APress
Edition:   1st ed.
Weight:   1.237kg
ISBN:  

9781484228715


ISBN 10:   1484228715
Pages:   638
Publication Date:   21 February 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1 Univariate Data Visualization2 Multivariate Data Visualization3 Generalized Linear Models 14 Generalized Linear Models 25 Generalized Additive Models6 Machine Learning: Introduction7 Machine Learning: Unsupervised8 Machine Learning: Supervised9 Missing Data10 Generalized Linear Mixed Models: Introduction11 Generalized Linear Mixed Models: Linear12 Generalized Linear Mixed Models: Advanced 13 Modeling IIVBibliography

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Author Information

Matt Wiley is a tenured, associate professor of mathematics with awards in both mathematics education and honour student engagement. He earned degrees in pure mathematics, computer science, and business administration through the University of California and Texas A&M systems. He serves as director for Victoria College’s quality enhancement plan and managing partner at Elkhart Group Limited, a statistical consultancy. With programming experience in R, C++, Ruby, Fortran, and JavaScript, he has always found ways to meld his passion for writing with his joy of logical problem solving and data science. From the boardroom to the classroom, Matt enjoys finding dynamic ways to partner with interdisciplinary and diverse teams to make complex ideas and projects understandable and solvable. Joshua F. Wiley is a lecturer in the Monash Institute for Cognitive and Clinical Neurosciences and School of Psychological Sciences at Monash University and a senior partner at Elkhart Group Limited, a statistical consultancy.  He earned his PhD from the University of California, Los Angeles, and his research focuses on using advanced quantitative methods to understand the complex interplays of psychological, social, and physiological processes in relation to psychological and physical health.  In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. Through consulting at Elkhart Group Limited and former work at the UCLA Statistical Consulting Group, he has supported a wide array of clients ranging from graduate students, to experienced researchers, and biotechnology companies.  He also develops or co-develops a number of R packages including varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.

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