Chapter 14. Asymptotic Theory for Parametric Models
Published Online: 26 MAR 2003
DOI: 10.1002/0471249688.ch14
Copyright © 2002 John Wiley & Sons, Inc.
Book Title
Categorical Data Analysis, Second Edition
Additional Information
How to Cite
Agresti, A. (2003) Asymptotic Theory for Parametric Models, in Categorical Data Analysis, Second Edition, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471249688.ch14
Publication History
- Published Online: 26 MAR 2003
- Published Print: 3 JUL 2002
Book Series:
ISBN Information
Print ISBN: 9780471360933
Online ISBN: 9780471249689
- Summary
- Chapter
Keywords:
- delta method;
- asymptotic normality;
- large-sample theory;
- residuals;
- goodness-of-fit statistics;
- chi-squared distribution;
- Pearson statistic;
- likelihood-ratio statistic
Summary
Chapter 14 surveys asymptotic theory for parametric models for contingency tables. It presents a detailed description of the delta method. It uses this to obtain asymptotic distributions of estimators of model parameters and cell probabilities, as well as asymptotic distributions of residuals and goodness-of-fit statistics. It illustrates this material by deriving asymptotic distributions for logit - loglinear models.