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Richly Parameterized Linear Models by Hodges James (33 results)
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hardcover. Condition: As New. Unmarked hardcover.
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Richly Parameterized Linear Models : Additive, Time Series, and Spatial Models Using Random Effects
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects
Language: English
Published by Taylor & Francis Ltd, 2021
ISBN 10: 0367533731 ISBN 13: 9780367533731
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Richly Parameterized Linear Models : Additive, Time Series, and Spatial Models Using Random Effects
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Richly Parameterized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects (Chapman & Hall/CRC Texts in Statistical Science)
Language: English
Published by Routledge 2021-06-30, 2021
ISBN 10: 0367533731 ISBN 13: 9780367533731
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Paperback. Condition: Brand New. 469 pages. 9.21x6.14x1.02 inches. In Stock.
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Richly Parameterized Linear Models | Additive, Time Series, and Spatial Models Using Random Effects
Language: English
Published by Chapman and Hall/CRC, 2021
ISBN 10: 0367533731 ISBN 13: 9780367533731
Taschenbuch. Condition: Neu. Richly Parameterized Linear Models | Additive, Time Series, and Spatial Models Using Random Effects | James S. Hodges | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | Chapman and Hall/CRC | EAN 9780367533731 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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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
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects
Language: English
Published by Taylor & Francis Inc, 2013
ISBN 10: 143986683X ISBN 13: 9781439866832
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. New copy - Usually dispatched within 4 working days.
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Richly Parameterized Linear Models
Language: English
Published by Taylor & Francis Group, 2013
ISBN 10: 143986683X ISBN 13: 9781439866832
Condition: New. pp. 469 1st Edition.
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Richly Parameterized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
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Richly Parameterized Linear Models
Language: English
Published by Taylor & Francis Group, 2013
ISBN 10: 143986683X ISBN 13: 9781439866832
Condition: New. pp. 469.
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Richly Parameterized Linear Models
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Richly Parameterized Linear Models
Language: English
Published by Chapman And Hall/CRC Jun 2021, 2021
ISBN 10: 0367533731 ISBN 13: 9780367533731
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. 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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Condition: 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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Richly Parameterized Linear Models : Additive, Time Series, and Spatial Models Using Random Effects
Language: English
Published by Chapman And Hall/CRC, 2021
ISBN 10: 0367533731 ISBN 13: 9780367533731
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.
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Richly Parameterized Linear Models
Language: English
Published by Taylor & Francis Group, 2013
ISBN 10: 143986683X ISBN 13: 9781439866832
Condition: New. pp. 469 This item is printed on demand.
-
Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects
Language: English
Published by Taylor & Francis Inc, 2013
ISBN 10: 143986683X ISBN 13: 9781439866832
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 137.84
£ 15.75 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Gebunden. Condition: 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 prob.
