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Regression analysis of count data / A. Colin Cameron, Pravin K. Trivedi.

By: Contributor(s): Material type: TextTextSeries: Econometric Society monographs ; no. 30.Publication details: Cambridge, UK ; New York, NY, USA : Cambridge University Press, 1998.Description: 1 online resource (xvii, 411 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 0511066147
  • 9780511066146
  • 0511068271
  • 9780511068270
  • 0511117094
  • 9780511117091
  • 9780511814365
  • 0511814364
Subject(s): Genre/Form: Additional physical formats: Print version:: Regression analysis of count data.DDC classification:
  • 519.5/36 21
LOC classification:
  • QA278.2 .C36 1998eb
Online resources:
Contents:
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 App. B. Functions, Distributions, and Moments App. C. Software.
Summary: Students in both the natural and social sciences often seek regression models to explain the frequency of events, such as visits to a doctor. This analysis provides the most comprehensive and up-to-date account of models and methods to interpret such data.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Mathematics Available
Total holds: 0

Includes bibliographical references (pages 379-398) and indexes.

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 App. B. Functions, Distributions, and Moments App. C. Software.

Students in both the natural and social sciences often seek regression models to explain the frequency of events, such as visits to a doctor. This analysis provides the most comprehensive and up-to-date account of models and methods to interpret such data.

Print version record.

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