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Advanced Linear Modeling: Statistical Learning and Dependent Data

-15% su kodu: ENG15
112,18 
Įprasta kaina: 131,98 
-15% su kodu: ENG15
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Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
112,18 
Įprasta kaina: 131,98 
-15% su kodu: ENG15
Kupono kodas: ENG15
Akcija baigiasi: 2025-03-03
-15% su kodu: ENG15
2025-02-28 131.9800 InStock
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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: 2021
Knygos puslapių skaičius: 632
ISBN-10: 3030291669
ISBN-13: 9783030291662
Formatas: 235 x 155 x 34 mm. Knyga minkštu viršeliu
Kalba: Anglų

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