Advanced Linear Modeling - Statistical Learning and Dependent Data (Paperback, 3rd ed. 2019)

This book introduces several topics related to linear model theory, including: multivariate linear models, discriminant analysis, principal components, factor analysis, time series in both the frequency and time domains, and spatial data analysis. This second edition adds new material on nonparametric regression, response surface maximization, and longitudinal models. The book provides a unified approach to these disparate subjects and serves as a self-contained companion volume to the author's Plane Answers to Complex Questions: The Theory of Linear Models. Ronald Christensen is Professor of Statistics at the University of New Mexico. He is well known for his work on the theory and application of linear models having linear structure.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Texts in Statistics
Release date:	2021
First published:	2019
Authors:	Ronald Christensen
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	608
Edition:	3rd ed. 2019
ISBN-13:	978-3-03-029166-2
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics
LSN:	3-03-029166-9
Barcode:	9783030291662

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