Brian j reich (35 risultati)
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2019
Serie: Libro 59 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2019
Serie: Libro 59 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Books Liquidation, Sacramento, CA, U.S.A.Books Liquidation
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hardcover. Condizione: Acceptable. Readable condition, all page intact, has wear, some writing or highlighting inside.
Lingua: Inglese
Editore: CRC Press LLC, 2019
Serie: Libro 59 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Better World Books, Mishawaka, IN, U.S.A.Better World Books
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EUR 34,99
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Condizione: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Lingua: Inglese
Editore: Routledge, 2021
Serie: Libro 59 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Textbooks_Source, Columbia, MO, U.S.A.Textbooks_Source
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paperback. Condizione: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 114,87
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Condizione: New.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 113,69
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Condizione: New.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 113,25
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Condizione: New.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 114,65
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Condizione: New.
Lingua: Inglese
Editore: CRC Press, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 111,69
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Condizione: New.
Lingua: Inglese
Editore: CRC Press, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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EUR 123,54
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: CRC Press, 2019
Serie: Libro 59 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Anybook.com, Lincoln, Regno UnitoAnybook.com
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Condizione: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780815378648.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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EUR 130,37
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Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: California Books, Miami, FL, U.S.A.California Books
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EUR 134,76
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Condizione: New.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Chiron Media, Wallingford, Regno UnitoChiron Media
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EUR 116,73
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hardcover. Condizione: New.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 130,89
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Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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Condizione: New. 2026. 2nd Edition. hardcover. . . . . .
Lingua: Inglese
Editore: Taylor & Francis Ltd, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 131,40
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA
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EUR 158,34
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Hardback. Condizione: New. Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, this book is more focused on Bayesian methods applied routinely in practice, including multiple linear…regression, mixed effects models and generalized linear models. This second edition includes a new chapter on Bayesian machine learning methods to handle large and complex datasets and several new applications to illustrate the benefits of the Bayesian approach in terms of uncertainty quantification. Readers familiar with only introductory statistics will find this book accessible, as it includes many worked examples with complete R code, and comparisons are presented with analogous frequentist procedures. The book can be used as a one-semester course for advanced undergraduate and graduate students and can be used in courses comprising undergraduate statistics majors, as well as non-statistics graduate students from other disciplines such as engineering, ecology and psychology. In addition to thorough treatment of the basic concepts of Bayesian inferential methods, the book covers many general topics:Advice on selecting prior distributionsComputational methods including Markov chain Monte Carlo (MCMC) samplingModel-comparison and goodness-of-fit measures, including sensitivity to priors.To illustrate the flexibility of the Bayesian approaches for complex data structures, the latter chapters provide case studies covering advanced topics:Handling of missing and censored dataPriors for high-dimensional regression modelsMachine learning models including Bayesian adaptive regression trees and deep learningComputational techniques for large datasetsFrequentist properties of Bayesian methods.The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets and complete data analyses is made available on the book's website.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Speedyhen, Hertfordshire, Regno UnitoSpeedyhen
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EUR 111,70
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Condizione: NEW.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Rarewaves.com USA, London, LONDO, Regno UnitoRarewaves.com USA
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EUR 173,33
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Hardback. Condizione: New. Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, this book is more focused on Bayesian methods applied routinely in practice, including multiple linear…regression, mixed effects models and generalized linear models. This second edition includes a new chapter on Bayesian machine learning methods to handle large and complex datasets and several new applications to illustrate the benefits of the Bayesian approach in terms of uncertainty quantification. Readers familiar with only introductory statistics will find this book accessible, as it includes many worked examples with complete R code, and comparisons are presented with analogous frequentist procedures. The book can be used as a one-semester course for advanced undergraduate and graduate students and can be used in courses comprising undergraduate statistics majors, as well as non-statistics graduate students from other disciplines such as engineering, ecology and psychology. In addition to thorough treatment of the basic concepts of Bayesian inferential methods, the book covers many general topics:Advice on selecting prior distributionsComputational methods including Markov chain Monte Carlo (MCMC) samplingModel-comparison and goodness-of-fit measures, including sensitivity to priors.To illustrate the flexibility of the Bayesian approaches for complex data structures, the latter chapters provide case studies covering advanced topics:Handling of missing and censored dataPriors for high-dimensional regression modelsMachine learning models including Bayesian adaptive regression trees and deep learningComputational techniques for large datasetsFrequentist properties of Bayesian methods.The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets and complete data analyses is made available on the book's website.
Lingua: Inglese
Editore: Chapman and Hall/CRC, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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EUR 166,98
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Condizione: New. 2026. 2nd Edition. hardcover. . . . . . Books ship from the US and Ireland.
Lingua: Inglese
Editore: CRC Press, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: moluna, Greven, Germaniamoluna
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EUR 138,15
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Condizione: New. Brian J. Reich, Gertrude M. Cox Distinguished Professor of Statistics at North Carolina State University, applies Bayesian statistical methods in a variety of fields including environmental epidemiology, engineering, weather and climate.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United
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EUR 161,32
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Hardback. Condizione: New. Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, this book is more focused on Bayesian methods applied routinely in practice, including multiple linear…regression, mixed effects models and generalized linear models. This second edition includes a new chapter on Bayesian machine learning methods to handle large and complex datasets and several new applications to illustrate the benefits of the Bayesian approach in terms of uncertainty quantification. Readers familiar with only introductory statistics will find this book accessible, as it includes many worked examples with complete R code, and comparisons are presented with analogous frequentist procedures. The book can be used as a one-semester course for advanced undergraduate and graduate students and can be used in courses comprising undergraduate statistics majors, as well as non-statistics graduate students from other disciplines such as engineering, ecology and psychology. In addition to thorough treatment of the basic concepts of Bayesian inferential methods, the book covers many general topics:Advice on selecting prior distributionsComputational methods including Markov chain Monte Carlo (MCMC) samplingModel-comparison and goodness-of-fit measures, including sensitivity to priors.To illustrate the flexibility of the Bayesian approaches for complex data structures, the latter chapters provide case studies covering advanced topics:Handling of missing and censored dataPriors for high-dimensional regression modelsMachine learning models including Bayesian adaptive regression trees and deep learningComputational techniques for large datasetsFrequentist properties of Bayesian methods.The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets and complete data analyses is made available on the book's website.
Lingua: Inglese
Editore: Chapman & Hall, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 198,23
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Hardcover. Condizione: Brand New. 2nd edition. 360 pages. 10.00x7.00x10.24 inches. In Stock.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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EUR 169,72
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Hardback. Condizione: New. Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, this book is more focused on Bayesian methods applied routinely in practice, including multiple linear…regression, mixed effects models and generalized linear models. This second edition includes a new chapter on Bayesian machine learning methods to handle large and complex datasets and several new applications to illustrate the benefits of the Bayesian approach in terms of uncertainty quantification. Readers familiar with only introductory statistics will find this book accessible, as it includes many worked examples with complete R code, and comparisons are presented with analogous frequentist procedures. The book can be used as a one-semester course for advanced undergraduate and graduate students and can be used in courses comprising undergraduate statistics majors, as well as non-statistics graduate students from other disciplines such as engineering, ecology and psychology. In addition to thorough treatment of the basic concepts of Bayesian inferential methods, the book covers many general topics:Advice on selecting prior distributionsComputational methods including Markov chain Monte Carlo (MCMC) samplingModel-comparison and goodness-of-fit measures, including sensitivity to priors.To illustrate the flexibility of the Bayesian approaches for complex data structures, the latter chapters provide case studies covering advanced topics:Handling of missing and censored dataPriors for high-dimensional regression modelsMachine learning models including Bayesian adaptive regression trees and deep learningComputational techniques for large datasetsFrequentist properties of Bayesian methods.The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets and complete data analyses is made available on the book's website.
- Rilegato
Da: Chiron Media, Wallingford, Regno UnitoChiron Media
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EUR 572,88
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Hardcover. Condizione: New.
Lingua: Inglese
Editore: CRC Press, 2021
Serie: Libro 59 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Brossura
- Print on Demand
Da: moluna, Greven, Germaniamoluna
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EUR 51,38
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Brian J. Reich, Associate Professor of Statistics at North Carolina State University, is currently the editor-in-chief of the Journal of Agricultural, Biological, and Environmental Statistics and was awarded the LeRo…y & Elva M.
Lingua: Inglese
Editore: CRC Press, 2019
Serie: Libro 59 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 102,65
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practi…ce including multiple linear re.
Lingua: Inglese
Editore: Taylor & Francis Ltd, 2026
Serie: Libro 112 di 59 - Chapman & Hall/CRC Texts in Statistical Science
- Rilegato
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 158,30
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Hardcover. Condizione: new. Hardcover. Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, this book is more focused on Bayesian methods applied routinely in practice, including mult…iple linear regression, mixed effects models and generalized linear models. This second edition includes a new chapter on Bayesian machine learning methods to handle large and complex datasets and several new applications to illustrate the benefits of the Bayesian approach in terms of uncertainty quantification. Readers familiar with only introductory statistics will find this book accessible, as it includes many worked examples with complete R code, and comparisons are presented with analogous frequentist procedures. The book can be used as a one-semester course for advanced undergraduate and graduate students and can be used in courses comprising undergraduate statistics majors, as well as non-statistics graduate students from other disciplines such as engineering, ecology and psychology. In addition to thorough treatment of the basic concepts of Bayesian inferential methods, the book covers many general topics:Advice on selecting prior distributionsComputational methods including Markov chain Monte Carlo (MCMC) samplingModel-comparison and goodness-of-fit measures, including sensitivity to priors.To illustrate the flexibility of the Bayesian approaches for complex data structures, the latter chapters provide case studies covering advanced topics:Handling of missing and censored dataPriors for high-dimensional regression modelsMachine learning models including Bayesian adaptive regression trees and deep learningComputational techniques for large datasetsFrequentist properties of Bayesian methods.The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets and complete data analyses is made available on the books website. This book provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, it is more focused on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
