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Richly Parameterized Linear Models by Hodges James (37 results)
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Richly Parameterized Linear Models : Additive, Time Series, and Spatial Models Using Random Effects
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Richly Parameterized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects
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Richly Parameterized Linear Models : Additive, Time Series, and Spatial Models Using Random Effects
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects (Chapman & Hall/CRC Texts in Statistical Science)
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ISBN 10: 143986683X ISBN 13: 9781439866832
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Richly Parameterized Linear Models : Additive, Time Series, and Spatial Models Using Random Effects
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects
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Richly Parameterized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
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Richly Parameterized Linear Models
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ISBN 10: 143986683X ISBN 13: 9781439866832
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Richly Parameterized Linear Models : Additive, Time Series, and Spatial Models Using Random Effects
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Richly Parameterized Linear Models
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Richly Parameterized Linear Models
Published by Chapman And Hall/CRC Jun 2021, 2021
ISBN 10: 0367533731 ISBN 13: 9780367533731
Language: English
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A First Step toward a Unified Theory of Richly Parameterized Linear ModelsUsing mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based understanding of models with random effects.Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects takes a first step in developing a full theory of richly parameterized models, which would allow statisticians to better understand their analysis results. The author examines what is known and unknown about mixed linear models and identifies research opportunities.The first two parts of the book cover an existing syntax for unifying models with random effects. The text explains how richly parameterized models can be expressed as mixed linear models and analyzed using conventional and Bayesian methods.In the last two parts, the author discusses oddities that can arise when analyzing data using these models. He presents ways to detect problems and, when possible, shows how to mitigate or avoid them. The book adapts ideas from linear model theory and then goes beyond that theory by examining the information in the data about the mixed linear model's covariance matrices.Each chapter ends with two sets of exercises. Conventional problems encourage readers to practice with the algebraic methods and open questions motivate readers to research further. Supporting materials, including datasets for most of the examples analyzed, are available on the author's website. 470 pp. Englisch.
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Richly Parameterized Linear Models
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. James S. HodgesA First Step toward a Unified Theory of Richly Parameterized Linear ModelsUsing mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the .
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