Modeling Count Data

Modeling Count Data PDF Author: Joseph M. Hilbe
Publisher: Cambridge University Press
ISBN: 1107028337
Category : Business & Economics
Languages : en
Pages : 301

Book Description
This book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models.

Regression Analysis of Count Data

Regression Analysis of Count Data PDF Author: Adrian Colin Cameron
Publisher: Cambridge University Press
ISBN: 1107014166
Category : Business & Economics
Languages : en
Pages : 597

Book Description
This book provides the most comprehensive and up-to-date account of regression methods to explain the frequency of events.

Econometric Analysis of Count Data

Econometric Analysis of Count Data PDF Author: Rainer Winkelmann
Publisher: Springer Science & Business Media
ISBN: 9783540404040
Category : Business & Economics
Languages : en
Pages : 324

Book Description
Many other sections have been entirely rewritten and extended."--BOOK JACKET.

Negative Binomial Regression

Negative Binomial Regression PDF Author: Joseph M. Hilbe
Publisher: Cambridge University Press
ISBN: 1139500066
Category : Mathematics
Languages : en
Pages : 573

Book Description
This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation and evaluation. Complete Stata and R codes are provided throughout the text, with additional code (plus SAS), derivations and data provided on the book's website. Written for the practising researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluating count data.

Regression Models for Categorical and Limited Dependent Variables

Regression Models for Categorical and Limited Dependent Variables PDF Author: J. Scott Long
Publisher: SAGE
ISBN: 9780803973749
Category : Mathematics
Languages : en
Pages : 334

Book Description
Evaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c.

Count Data Models

Count Data Models PDF Author: Rainer Winkelmann
Publisher: Springer Science & Business Media
ISBN: 366221735X
Category : Business & Economics
Languages : en
Pages : 223

Book Description
This book presents statistical methods for the analysis of events. The primary focus is on single equation cross section models. The book addresses both the methodology and the practice of the subject and it provides both a synthesis of a diverse body of literature that hitherto was available largely in pieces, as well as a contribution to the progress of the methodology, establishing several new results and introducing new models. Starting from the standard Poisson regression model as a benchmark, the causes, symptoms and consequences of misspecification are worked out. Both parametric and semi-parametric alternatives are discussed. While semi-parametric models allow for robust interference, parametric models can identify features of the underlying data generation process.

International Encyclopedia of Statistical Science

International Encyclopedia of Statistical Science PDF Author: Miodrag Lovric
Publisher: Springer Science & Business Media
ISBN: 3642048978
Category : Mathematics
Languages : en
Pages : 0

Book Description
The goal of this book is multidimensional: a) to help reviving Statistics education in many parts in the world where it is in crisis. For the first time authors from many developing countries have an opportunity to write together with the most prominent world authorities. The editor has spent several years searching for the most reputable statisticians all over the world. International contributors are either presidents of the local statistical societies, or head of the Statistics department at the main university, or the most distinguished statisticians in their countries. b) to enable any non-statistician to obtain quick and yet comprehensive and highly understandable view on certain statistical term, method or application c) to enable all the researchers, managers and practicioners to refresh their knowledge in Statistics, especially in certain controversial fields. d) to revive interest in statistics among students, since they will see its usefulness and relevance in almost all branches of Science.

Regression & Linear Modeling

Regression & Linear Modeling PDF Author: Jason W. Osborne
Publisher: SAGE Publications
ISBN: 1506302750
Category : Psychology
Languages : en
Pages : 489

Book Description
In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.

Mixed Effects Models and Extensions in Ecology with R

Mixed Effects Models and Extensions in Ecology with R PDF Author: Alain Zuur
Publisher: Springer Science & Business Media
ISBN: 0387874585
Category : Science
Languages : en
Pages : 579

Book Description
This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.
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