Statistical Regression Modeling with R is popular PDF and ePub book, written by Ding-Geng (Din) Chen in 2021-04-08, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Statistical Regression Modeling with R can be Read Online from any device for your convenience.
Statistical Regression Modeling with R Book PDF Summary
This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.
Detail Book of Statistical Regression Modeling with R PDF
- Author : Ding-Geng (Din) Chen
- Release : 08 April 2021
- Publisher : Springer Nature
- ISBN : 9783030675837
- Genre : Mathematics
- Total Page : 239 pages
- Language : English
- PDF File Size : 10,7 Mb
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