Overview
- It is accompanied by the web-site: semiparametric-regression-with-r.net and contains pointers to datasets and R code relevant to this book
- This book helps to close the gap between the available methodology and their use in practice
- Because of its flexibility, semiparametric regression has proven to be of great value in many applications in fields as diverse as astronomy, biology, medicine, economics and finance
Part of the book series: Use R! (USE R)
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Table of contents (6 chapters)
Keywords
About this book
The authors assemble a broad range of semiparametric regression R analyses and put them in a form that is useful for applied researchers. There are chapters devoted to penalized spines, generalized additive models, grouped data, bivariate extensions of penalized spines, and spatial semi-parametric regression models. Where feasible, the R code is provided in the text, however the book is also accompanied by an external website complete with datasets and R code. Because of its flexibility, semiparametric regression has proven to be of great value with many applications in fields as diverse as astronomy, biology, medicine, economics, and finance. This book is intended for applied statistical analysts who have some familiarity with R.
Authors and Affiliations
About the authors
Jaroslaw Harezlak is Associate Professor in the Department of Epidemiology and Biostatistics at the Indiana University School of Public Health in Bloomington. He has a Ph.D. in biostatistics from the Harvard University. After a 2-year post-doctoral training at the Harvard School of Public Health, he joined Indiana University as an Assistant Professor. His interests span a number of medical areas: including NeuroHIV, physical activity, sexually transmitted infections, and concussions, as well as statistical areas: including semiparametric regression, functional data analysis and structured high-dimensional data. In his applied research, he uses data arising in structural and functional brain imaging, accelerometry, and intensively collected longitudinal studies. He has published over 50 peer-reviewed articles in the statistical, medical and epidemiological journals as well as 3 invited chapters.
Matt Wand is Distinguished Professor of Statistics at University of Technology Sydney. He serves as an associate editor for the Statistics journal: Australian and New Zealand Journal of Statistics. Professor Wand is chiefly interested in the development of statistical methodology for finding useful structure in large multivariate data sets. Currently, Wand’s specific interests include expectation propagation, message passing algorithms, variational approximate methods, statistical methods for streaming data, generalized linear mixed models, and semiparametric regression.
Bibliographic Information
Book Title: Semiparametric Regression with R
Authors: Jaroslaw Harezlak, David Ruppert, Matt P. Wand
Series Title: Use R!
DOI: https://doi.org/10.1007/978-1-4939-8853-2
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2018
Softcover ISBN: 978-1-4939-8851-8Published: 13 December 2018
eBook ISBN: 978-1-4939-8853-2Published: 12 December 2018
Series ISSN: 2197-5736
Series E-ISSN: 2197-5744
Edition Number: 1
Number of Pages: XI, 331
Number of Illustrations: 2 b/w illustrations, 142 illustrations in colour
Topics: Statistical Theory and Methods, Statistics for Life Sciences, Medicine, Health Sciences, Statistics for Business, Management, Economics, Finance, Insurance