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Statistical methods for overdisperse...

Dupuy, Jean-François,

Statistical methods for overdispersed count data

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical methods for overdispersed count dataJean-François Dupuy.
作者:	Dupuy, Jean-François,
出版者:	London, UK :ISTE Press Ltd ;2018.
面頁冊數:	1 online resource.
標題:	Linear models (Statistics)
電子資源:	https://www.sciencedirect.com/science/book/9781785482663
ISBN:	9780081023747 (electronic bk.)

Statistical methods for overdispersed count data
Dupuy, Jean-François,

Statistical methods for overdispersed count data[electronic resource] /Jean-François Dupuy. - London, UK :ISTE Press Ltd ;2018. - 1 online resource. - Biostatistics and health science set. - Biostatistics and health science set (Series).

Includes bibliographical references and index.

Front Cover; Statistical Methods for Overdispersed Count Data; Copyright Page; Contents; Introduction; 1. Brief Overview of Linear Models; 1.1. Introduction; 1.2. The standard linear model; 1.3. Least squares estimator; 1.4. The Gaussian linear model; 1.5. Linear models in R; 1.6. Asymptotic properties; 2. Generalized Linear Models; 2.1. Exponential families; 2.2. The components of a generalized linear model; 2.3. Maximum likelihood estimator; 2.4. Binomial regression; 2.5. Poisson regression; 2.6. Generalized linear models in R; 3. Overdispersion in Count Data; 3.1. Introduction

ISBN: 9780081023747 (electronic bk.)Subjects--Topical Terms:

181866
Linear models (Statistics)
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Statistical methods for overdispersed count data
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504 $a Includes bibliographical references and index.
505 0 $a Front Cover; Statistical Methods for Overdispersed Count Data; Copyright Page; Contents; Introduction; 1. Brief Overview of Linear Models; 1.1. Introduction; 1.2. The standard linear model; 1.3. Least squares estimator; 1.4. The Gaussian linear model; 1.5. Linear models in R; 1.6. Asymptotic properties; 2. Generalized Linear Models; 2.1. Exponential families; 2.2. The components of a generalized linear model; 2.3. Maximum likelihood estimator; 2.4. Binomial regression; 2.5. Poisson regression; 2.6. Generalized linear models in R; 3. Overdispersion in Count Data; 3.1. Introduction
505 8 $a 3.2. The quasi-Poisson model3.3. The negative binomial regression model; 3.4. Application to the NMES1988 data; 4. Count Data and Zero Inflation; 4.1. Introduction; 4.2. ZIP regression model; 4.3. ZIB regression model; 4.4. Example of an application of the ZIP and ZIB models in healthcare economics; 4.5. ZIM regression model; References; Index; Back Cover
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