A First Course in Linear Model Theory

by Paul Fuhrmann (Author), Uwe Helmke (Author)

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models.

Differential Galois theory has seen intense research activity during the last decades in several directions: elaboration of more general theories, computational aspects, model theoretic approaches, applications to classical and quantum mechanics as well as to other mathematical areas such as number theory.

4-in-1 Bundle covering the 4 essential topics for a data scientist - SQL, Tableau, Machine & Deep Learning using Python

Become a professional Data Scientist with R and learn Machine Learning, Data Analysis + Visualization, Web Apps + more!