A first course in linear model theory
by Ravishanker, Nalini, Dey, Dipak
fromTexts in statistical science
This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an innovative approach, the author's introduces students to the …
This book provides a practical guide for the use of modern statistical methods within agricultural and natural resources sciences. Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences is being released world-wide at an important time of …
"Over the past 15 years there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method with the aim of showing how it provides a unifying approach to a wide range of s…
"Over the past 15 years there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method with the aim of showing how it provides a unifying approach to a wide range of s…
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data …
Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two- or higher- dimensional, thus an understanding of Statistics in on…
