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Titlebook: Advanced Linear Modeling; Statistical Learning Ronald Christensen Textbook 2019Latest edition Springer Nature Switzerland AG 2019 ANOVA.Exc

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發(fā)表于 2025-3-21 19:28:12 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advanced Linear Modeling
期刊簡稱Statistical Learning
影響因子2023Ronald Christensen
視頻videohttp://file.papertrans.cn/146/145829/145829.mp4
發(fā)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
學(xué)科分類Springer Texts in Statistics
圖書封面Titlebook: Advanced Linear Modeling; Statistical Learning Ronald Christensen Textbook 2019Latest edition Springer Nature Switzerland AG 2019 ANOVA.Exc
影響因子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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Frequency Analysis of Time Series,duction is helpful for policymakers, researchers, students, and other people to upgrade life quality. Such knowledge is valuable because it is up-to-date, generalizable, and sensible based on the analytic-functionalist theoretical framework and statistical estimation.
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Linear Models for Spatial Data: Kriging,e theory we develop in this chapter will provide the basis for the nonparametric models of technology developed in Chapter 4 and the efficiency and productivity analysis undertaken in Parts II and III.
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1431-875X ers. 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..978-3-030-29166-2978-3-030-29164-8Series ISSN 1431-875X Series E-ISSN 2197-4136
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Generalized Multivariate Linear Models and Longitudinal Data,n of adaptive concepts, which are capable of placing computational resources automatically where needed to realize the desired quality of the solution, e.g. in terms of error tolerances, at the lowest computational effort.
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Mixed Models and Variance Components, greater. Improved knowledge of mechanisms, signaling pathways, and molecular interactions with the digestive tract and host organism is necessary to exploit the potential of the microbiome to stabilize animal health.
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