Cepeda Cuervo Edilberto (17 results)
- Hardcover
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- Hardcover
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- Hardcover
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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- Hardcover
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Hardcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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- Hardcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
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- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 160 pages. 9.18x6.12x9.45 inches. In Stock.
- Softcover
Seller: moluna, Greven, Germanymoluna
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- Hardcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Hardcover. Condition: new. Hardcover. This book provides an introduction to double generalized linear models (DGLMs) under frequentist and Bayesian frameworks. These models include the class of generalized linear models and compose a unified class of models, where appropriate functions of the mean and dispersion parameters follo…w linear regression structures that are linear combinations of the explanatory variables. The heteroscedastic normal linear regression models, gamma regression models (where both mean and shape have regression structures), and beta regression models (where both mean and dispersion have regression structures) are examples of this family of regression models. A central topic in the framework of DGLMs is count overdispersion regression models, specifically those associated with the Poisson and binomial distributions. An extension of double generalized linear models is the family of double generalized nonlinear models.Features: Covers generalized linear models and double generalized linear models under frequentist and Bayesian approaches Presents normal heteroscedastic linear regression models as an introduction to double generalized linear models Defines double generalized linear regression models under frequentist and Bayesian perspectives, including as examples the beta and the gamma regression models Presents models with overdispersion along with frequentist and Bayesian estimation methodsThe book is primarily aimed at researchers and graduate students of statistics and mathematics. Provides an introduction to double generalized linear models (DGLMs), under frequentist and Bayesian frameworks. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Hardcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
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Hardcover. Condition: new. Hardcover. This book provides an introduction to double generalized linear models (DGLMs) under frequentist and Bayesian frameworks. These models include the class of generalized linear models and compose a unified class of models, where appropriate functions of the mean and dispersion parameters follo…w linear regression structures that are linear combinations of the explanatory variables. The heteroscedastic normal linear regression models, gamma regression models (where both mean and shape have regression structures), and beta regression models (where both mean and dispersion have regression structures) are examples of this family of regression models. A central topic in the framework of DGLMs is count overdispersion regression models, specifically those associated with the Poisson and binomial distributions. An extension of double generalized linear models is the family of double generalized nonlinear models.Features: Covers generalized linear models and double generalized linear models under frequentist and Bayesian approaches Presents normal heteroscedastic linear regression models as an introduction to double generalized linear models Defines double generalized linear regression models under frequentist and Bayesian perspectives, including as examples the beta and the gamma regression models Presents models with overdispersion along with frequentist and Bayesian estimation methodsThe book is primarily aimed at researchers and graduate students of statistics and mathematics. Provides an introduction to double generalized linear models (DGLMs), under frequentist and Bayesian frameworks. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Hardcover
- Print on Demand
Seller: preigu, Osnabrück, Germanypreigu
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US$ 204.03
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Buch. Condition: Neu. Double Generalized Linear Models | Likelihood and Bayesian Methods | Edilberto Cepeda-Cuervo | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Chapman and Hall/CRC | EAN 9781041169970 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: p…reigu Print on Demand.
- Hardcover
- Print on Demand
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contact seller5-star sellerCondition: New
US$ 256.37
US$ 37.00 shippingShips from Australia to U.S.A.Quantity: 1 available
Hardcover. Condition: new. Hardcover. This book provides an introduction to double generalized linear models (DGLMs) under frequentist and Bayesian frameworks. These models include the class of generalized linear models and compose a unified class of models, where appropriate functions of the mean and dispersion parameters follo…w linear regression structures that are linear combinations of the explanatory variables. The heteroscedastic normal linear regression models, gamma regression models (where both mean and shape have regression structures), and beta regression models (where both mean and dispersion have regression structures) are examples of this family of regression models. A central topic in the framework of DGLMs is count overdispersion regression models, specifically those associated with the Poisson and binomial distributions. An extension of double generalized linear models is the family of double generalized nonlinear models.Features: Covers generalized linear models and double generalized linear models under frequentist and Bayesian approaches Presents normal heteroscedastic linear regression models as an introduction to double generalized linear models Defines double generalized linear regression models under frequentist and Bayesian perspectives, including as examples the beta and the gamma regression models Presents models with overdispersion along with frequentist and Bayesian estimation methodsThe book is primarily aimed at researchers and graduate students of statistics and mathematics. Provides an introduction to double generalized linear models (DGLMs), under frequentist and Bayesian frameworks. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
