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Introduction to General and Generalized Linear Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Introduction to General and Generalized Linear Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Introduction to General and Generalized Linear Models
Language: English
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032922362 ISBN 13: 9781032922362
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Introduction to General and Generalized Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
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Introduction To General And Generalized Linear Models
Language: English
Published by Crc Press, 2020
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Paperback. Condition: Brand New. 316 pages. 9.18x6.12x0.59 inches. In Stock.
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Introduction to General and Generalized Linear Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Introduction to General and Generalized Linear Models
Language: English
Published by Taylor & Francis Group, 2010
ISBN 10: 1420091557 ISBN 13: 9781420091557
Condition: New. pp. 316.
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Introduction to General and Generalized Linear Models
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Introduction to General and Generalized Linear Models
Language: English
Published by Taylor & Francis Inc, 2010
ISBN 10: 1420091557 ISBN 13: 9781420091557
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Introduction to General and Generalized Linear Models
Language: English
Published by Taylor & Francis Group, 2010
ISBN 10: 1420091557 ISBN 13: 9781420091557
Condition: New. pp. 316.
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Introduction to General and Generalized Linear Models
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Introduction to General and Generalized Linear Models
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 -Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models presents likelihood-based techniques for statistical modelling using various types of data. Implementations using R are provided throughout the text, although other software packages are also discussed. Numerous examples show how the problems are solved with R.After describing the necessary likelihood theory, the book covers both general and generalized linear models using the same likelihood-based methods. It presents the corresponding/parallel results for the general linear models first, since they are easier to understand and often more well known. The authors then explore random effects and mixed effects in a Gaussian context. They also introduce non-Gaussian hierarchical models that are members of the exponential family of distributions. Each chapter contains examples and guidelines for solving the problems via R. Providing a flexible framework for data analysis and model building, this text focuses on the statistical methods and models that can help predict the expected value of an outcome, dependent, or response variable. It offers a sound introduction to general and generalized linear models using the popular and powerful likelihood techniques. Ancillary materials are available at imm.dtu.dk/~hm/GLM 318 pp. Englisch.
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Introduction to General and Generalized Linear Models
Language: English
Published by Taylor & Francis Group, 2010
ISBN 10: 1420091557 ISBN 13: 9781420091557
Condition: New. pp. 316 This item is printed on demand.
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Introduction to General and Generalized Linear Models
Language: English
Published by Taylor & Francis, CRC Press, 2010
ISBN 10: 1420091557 ISBN 13: 9781420091557
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models presents likelihood-based techniques for statistical modelling using various types of data. Implementations using R are provided throughout the text, although other software packages are also discussed. Numerous examples show how the problems are solved with R.After describing the necessary likelihood theory, the book covers both general and generalized linear models using the same likelihood-based methods. It presents the corresponding/parallel results for the general linear models first, since they are easier to understand and often more well known. The authors then explore random effects and mixed effects in a Gaussian context. They also introduce non-Gaussian hierarchical models that are members of the exponential family of distributions. Each chapter contains examples and guidelines for solving the problems via R. Providing a flexible framework for data analysis and model building, this text focuses on the statistical methods and models that can help predict the expected value of an outcome, dependent, or response variable. It offers a sound introduction to general and generalized linear models using the popular and powerful likelihood techniques. Ancillary materials are available at imm.dtu.dk/~hm/GLM 316 pp. Englisch.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models presents likelihood-based techniques for statistical modelling using various types of data. Implementations using R are provided throughout the text, although other software packages are also discussed. Numerous examples show how the problems are solved with R.After describing the necessary likelihood theory, the book covers both general and generalized linear models using the same likelihood-based methods. It presents the corresponding/parallel results for the general linear models first, since they are easier to understand and often more well known. The authors then explore random effects and mixed effects in a Gaussian context. They also introduce non-Gaussian hierarchical models that are members of the exponential family of distributions. Each chapter contains examples and guidelines for solving the problems via R. Providing a flexible framework for data analysis and model building, this text focuses on the statistical methods and models that can help predict the expected value of an outcome, dependent, or response variable. It offers a sound introduction to general and generalized linear models using the popular and powerful likelihood techniques. Ancillary materials are available at imm.dtu.dk/~hm/GLM.
-
Introduction to General and Generalized Linear Models
Language: English
Published by Taylor & Francis, CRC Press, 2010
ISBN 10: 1420091557 ISBN 13: 9781420091557
Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models presents likelihood-based techniques for statistical modelling using various types of data. Implementations using R are provided throughout the text, although other software packages are also discussed. Numerous examples show how the problems are solved with R.After describing the necessary likelihood theory, the book covers both general and generalized linear models using the same likelihood-based methods. It presents the corresponding/parallel results for the general linear models first, since they are easier to understand and often more well known. The authors then explore random effects and mixed effects in a Gaussian context. They also introduce non-Gaussian hierarchical models that are members of the exponential family of distributions. Each chapter contains examples and guidelines for solving the problems via R. Providing a flexible framework for data analysis and model building, this text focuses on the statistical methods and models that can help predict the expected value of an outcome, dependent, or response variable. It offers a sound introduction to general and generalized linear models using the popular and powerful likelihood techniques. Ancillary materials are available at imm.dtu.dk/~hm/GLM.
