Linear Models for Multivariate, Time Series, and Spatial Data (Springer Texts in Statistics) - Tapa dura

Libro 16 de 160: Springer Series in Statistics

Christensen, Ronald

 
9780387974132: Linear Models for Multivariate, Time Series, and Spatial Data (Springer Texts in Statistics)
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ISBN 10: 038797413X ISBN 13: 9780387974132
Editorial: Springer-Verlag New York Inc., 1997

Sinopsis

Book by Christensen Ronald

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Reseña del editor

A companion volume to Plane answers to complex questions: the theory of linear models (1987), presenting six chapters with shallow treatments of very broad topics showing how the properties of three fundamental ideas from standard linear model theory can be used to examine multivariate, time series,

Reseña del editor

This is a self-contained companion volume to the author's book "Plane Answers to Complex Questions: The Theory of Linear Models." It provides introductions to several topics related to linear model theory: multivariate linear models, discriminant analysis, principal components, factor analysis, time series in both the frequency and time domains, and spatial data analysis (geostatistics). The purpose of this volume is to use three fundamental ideas from linear model theory and exploit their properties in examining multivariate, time series and spatial data. The three ideas are: best linear prediction, projections, and Mahalanobis' distance. Multivariate linear models are viewed as linear models with a nondiagonal covariance matrix. Discriminant analysis is related to the Mahalanobis distance and multivariate analysis of variance. Principle components are best linear predictors. Frequency domain time series involves linear models with a peculiar design matrix. Time domain analysis involves models that are linear in the parameters but have random design matrices. Best linear predictors are used for forecasting time series and for estimation in time domain analysis. Spatial data analysis involves linear models in which the covariance matrix is modeled from the data and making best linear unbiased predictions of future observables. This book develops a unified approach to this wide ranging collection of problems. Ronald Christensen is Professor of Statistics at the University of New Mexico. He is recognized internationally as an expert in the theory and application of linear models. In addition to this book and "Plane Answers," he is the author of numerous research articles, "Log-LinearModels and Logistic Regression," and "Analysis of Variance, Design,

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Editorial
Springer-Verlag New York Inc.
Año de publicación
1997
Idioma
Inglés
ISBN 10 
038797413X
ISBN 13 
9780387974132
Encuadernación
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Número de páginas
336
Contacto del fabricante
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9783540974130: Linear Models for Multivariate, Time Series, and Spatial Data (Springer Texts in Statistics)

Edición Destacada

ISBN 10:  354097413X ISBN 13:  9783540974130
Editorial: Springer-Verlag Berlin and Heide..., 1997
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