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Advanced Linear Modeling: Statistical Learning and Dependent Data

181,48 
181,48 
2025-07-31 181.4800 InStock
Nemokamas pristatymas į paštomatus per 18-22 darbo dienų užsakymams nuo 19,00 

Knygos aprašymas

Now in its third edition, this companion volume to Ronald Christensen¿s Plane Answers to Complex Questions uses three fundamental concepts from standard linear model theory¿best linear prediction, projections, and Mahalanobis distance¿ to extend standard linear modeling into the realms of Statistical Learning and Dependent Data.

This new edition features a wealth of new and revised content. In Statistical Learning it delves into nonparametric regression, penalized estimation (regularization), reproducing kernel Hilbert spaces, the kernel trick, and support vector machines. For Dependent Data it uses linear model theory to examine general linear models, linear mixed models, time series, spatial data, (generalized) multivariate linear models, discrimination, and dimension reduction. While numerous references to Plane Answers are made throughout the volume, Advanced Linear Modeling can be used on its own given a solid background in linear models. Accompanying R code for the analyses is available online.

Informacija

Autorius: Ronald Christensen
Serija: Springer Texts in Statistics
Leidėjas: Springer Nature Switzerland
Išleidimo metai: 2019
Knygos puslapių skaičius: 632
ISBN-10: 3030291634
ISBN-13: 9783030291631
Formatas: Knyga kietu viršeliu
Kalba: Anglų
Žanras: Numerical analysis

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