Statistical Model

Use generalized linear mixed models to replace t-tests, ANOVA, regression, and more!

Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for statistical model fitting.

The application of digital signal processing (DSP) to problems in audio has been an area of growing importance since the pioneering DSP work of the 1960s and 70s. In the 1980s, DSP micro-chips became sufficiently powerful to handle the complex processing operations required for sound restoration in real-time, or close to real-time.

A large number of Mostellar's friends, colleagues, collaborators, and former students have contributed to the preparation of this volume in honor of his 70th birthday. It provides a critical assessment of Mosteller's professional and research contributions to the field of statistics and its applications.

Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model selection procedures. It thoroughly explains the concepts, illustrates the derivations of various Bayesian model selection criteria through examples, and provides R code for implementation.