| 期刊全称 | Advanced Linear Modeling | | 期刊简称 | Statistical Learning | | 影响因子2023 | Ronald Christensen | | 视频video | | | 发行地址 | Presents a collection of methodologies formulated and developed in the framework of linear models.Offers accompanying R code online for the included analyses.Features several new chapters, as well as | | 学科分类 | Springer Texts in Statistics | | 图书封面 |  | | 影响因子 | 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.. | | Pindex | Textbook 2019Latest edition |
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发表于 2025-3-21 19:28:12
