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Count Data Models


Count Data Models
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Econometric Analysis Of Count Data


Econometric Analysis Of Count Data
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Author : Rainer Winkelmann
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29

Econometric Analysis Of Count Data written by Rainer Winkelmann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Business & Economics categories.


The primary objective of this book is to provide an introduction to the econometric modeling of count data for graduate students and researchers. It should serve anyone whose interest lies either in developing the field fur ther, or in applying existing methods to empirical questions. Much of the material included in this book is not specific to economics, or to quantita tive social sciences more generally, but rather extends to disciplines such as biometrics and technometrics. Applications are as diverse as the number of congressional budget vetoes, the number of children in a household, and the number of mechanical defects in a production line. The unifying theme is a focus on regression models in which a dependent count variable is modeled as a function of independent variables which mayor may not be counts as well. The modeling of count data has come of age. Inclusion of some of the fundamental models in basic textbooks, and implementation on standard computer software programs bear witness to that. Based on the standard Poisson regression model, numerous extensions and alternatives have been developed to address the common challenges faced in empirical modeling (unobserved heterogeneity, selectivity, endogeneity, measurement error, and dependent observations in the context of panel data or multivariate data, to name but a few) as well as the challenges that are specific to count data (e. g. , over dispersion and underdispersion).



Regression Analysis Of Count Data


Regression Analysis Of Count Data
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Author : A. Colin Cameron
language : en
Publisher: Cambridge University Press
Release Date : 1998-09-28

Regression Analysis Of Count Data written by A. Colin Cameron and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-09-28 with Business & Economics categories.


This analysis provides a comprehensive account of models and methods to interpret frequency data.



Modeling Count Data


Modeling Count Data
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Author : Joseph M. Hilbe
language : en
Publisher: Cambridge University Press
Release Date : 2014-07-21

Modeling Count Data written by Joseph M. Hilbe and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-21 with Business & Economics categories.


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
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Author : Adrian Colin Cameron
language : en
Publisher: Cambridge University Press
Release Date : 2013-05-27

Regression Analysis Of Count Data written by Adrian Colin Cameron and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-27 with Business & Economics categories.


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



Regression Analysis Of Count Data


Regression Analysis Of Count Data
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Author : A. Colin Cameron
language : en
Publisher: Cambridge University Press
Release Date : 2013-05-27

Regression Analysis Of Count Data written by A. Colin Cameron and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-27 with Business & Economics categories.


Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. This book, now in its second edition, provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors combine theory and practice to make sophisticated methods of analysis accessible to researchers and practitioners working with widely different types of data and software in areas such as applied statistics, econometrics, marketing, operations research, actuarial studies, demography, biostatistics and quantitative social sciences. The new material includes new theoretical topics, an updated and expanded treatment of cross-section models, coverage of bootstrap-based and simulation-based inference, expanded treatment of time series, multivariate and panel data, expanded treatment of endogenous regressors, coverage of quantile count regression, and a new chapter on Bayesian methods.



Functional Form And Heterogeneity In Models For Count Data


Functional Form And Heterogeneity In Models For Count Data
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Author : William Greene
language : en
Publisher: Now Publishers Inc
Release Date : 2007

Functional Form And Heterogeneity In Models For Count Data written by William Greene and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Business & Economics categories.


This study presents several extensions of the most familiar models for count data, the Poisson and negative binomial models. We develop an encompassing model for two well-known variants of the negative binomial model (the NB1 and NB2 forms). We then analyze some alternative approaches to the standard log gamma model for introducing heterogeneity into the loglinear conditional means for these models. The lognormal model provides a versatile alternative specification that is more flexible (and more natural) than the log gamma form, and provides a platform for several "two part" extensions, including zero inflation, hurdle, and sample selection models. (We briefly present some alternative approaches to modeling heterogeneity.) We also resolve some features in Hausman, Hall and Griliches (1984, Economic models for count data with an application to the patents-R & D relationship, Econometrica 52, 909-938) widely used panel data treatments for the Poisson and negative binomial models that appear to conflict with more familiar models of fixed and random effects. Finally, we consider a bivariate Poisson model that is also based on the lognormal heterogeneity model. Two recent applications have used this model. We suggest that the correlation estimated in their model frameworks is an ambiguous measure of the correlation of the variables of interest, and may substantially overstate it. We conclude with a detailed application of the proposed methods using the data employed in one of the two aforementioned bivariate Poisson studies



Count Data Models


Count Data Models
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Author : Rainer Winkelmann
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11

Count Data Models written by Rainer Winkelmann and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Business & Economics categories.


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.



Specification And Estimation Of Count Data Regression And Sample Selection Models


Specification And Estimation Of Count Data Regression And Sample Selection Models
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Author : Lung-fei Lee
language : en
Publisher:
Release Date : 1996

Specification And Estimation Of Count Data Regression And Sample Selection Models written by Lung-fei Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with categories.




Count Data Models


Count Data Models
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Author : Rainer Winkelmann
language : en
Publisher:
Release Date : 2014-01-15

Count Data Models written by Rainer Winkelmann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.




Statistical Methods For Overdispersed Count Data


Statistical Methods For Overdispersed Count Data
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Author : Jean-Francois Dupuy
language : en
Publisher: Elsevier
Release Date : 2018-11-19

Statistical Methods For Overdispersed Count Data written by Jean-Francois Dupuy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-19 with Medical categories.


Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementation. All methods are illustrated on datasets arising in the field of health economics. As several tools have been developed to tackle over-dispersed and zero-inflated data (such as adjustment methods and zero-inflated models), this book covers the topic in a comprehensive and interesting manner. Includes reading on several levels, including methodology and applications Presents the state-of-the-art on the most recent zero-inflated regression models Contains a single dataset that is used as a common thread for illustrating all methodologies Includes R code that allows the reader to apply methodologies