Book contents
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface
- 1 Introduction
- 2 Model Specification and Estimation
- 3 Basic Count Regression
- 4 Generalized Count Regression
- 5 Model Evaluation and Testing
- 6 Empirical Illustrations
- 7 Time Series Data
- 8 Multivariate Data
- 9 Longitudinal Data
- 10 Measurement Errors
- 11 Nonrandom Samples and Simultaneity
- 12 Flexible Methods for Counts
- Appendices
- A Notation and Acronyms
- B Functions, Distributions, and Moments
- C Software
- References
- Author Index
- Subject Index
- Titles in the series
A - Notation and Acronyms
Published online by Cambridge University Press: 05 January 2013
- Frontmatter
- Contents
- List of Figures
- List of Tables
- Preface
- 1 Introduction
- 2 Model Specification and Estimation
- 3 Basic Count Regression
- 4 Generalized Count Regression
- 5 Model Evaluation and Testing
- 6 Empirical Illustrations
- 7 Time Series Data
- 8 Multivariate Data
- 9 Longitudinal Data
- 10 Measurement Errors
- 11 Nonrandom Samples and Simultaneity
- 12 Flexible Methods for Counts
- Appendices
- A Notation and Acronyms
- B Functions, Distributions, and Moments
- C Software
- References
- Author Index
- Subject Index
- Titles in the series
Summary
AIC: Akaike information criterion
ARMA: autoregressive moving average
BHHH: Berndt-Hall-Hall-Hausman algorithm
BIC: Bayes information criterion
BP: binary Poisson
Boot: bootstrap
CAIC: consistent Akaike information criterion
CB: correlated binomial
cdf: cumulative distribution function
CFMNB: slope-constrained finite mixture of negative binomials
CFMP: slope-constrained finite mixture of Poissons
CM: conditional moment (function or test)
- Type
- Chapter
- Information
- Regression Analysis of Count Data , pp. 371 - 373Publisher: Cambridge University PressPrint publication year: 1998