Generalized estimating equations have become increasingly popular in biometrical, econometrical and psychometrical applications. In this book, they are derived in a unified way using pseudo maximum likelihood estimation and the generalized method of moments.
Classical statistical theory is mainly the creation of two men: Ronald A. Fisher and Jerzy Neyman. This book explores the relationship between them, their interactions with other influential statisticians and the statistical history they helped create.
This text introduces general state space models in detail before focusing on dynamic linear models, emphasizing their Bayesian analysis. It illustrates all the fundamental steps needed to use dynamic linear models in practice, using R.
This book explains hazard-based analyses of competing risks and multistate data using the R statistical programming code, placing special emphasis on interpretation of results. Includes real data examples, and encourages readers to simulate their own data.
Business Analytics for Managers helps readers extract knowledge and actionable insight from real business data. The text emphasizes data-driven thinking and provides a quick-start guide to one of the most powerful software solutions available.
There has been a dramatic growth in the development and application of Bayesian inferential methods. This book introduces Bayesian modeling by the use of computation using the R language. The new edition contains changes in the R code illustrations.
The majority of data sets collected by researchers in all disciplines are multivariate. This book comprehensively covers a variety of multivariate analysis techniques using R. It provides extensive examples of R code used to apply the multivariate techniques.