Article
Licensed
Unlicensed
Requires Authentication
Asymptotic expansions for conditional moments of Bernoulli trials
-
Helmut Strasser
Published/Copyright:
November 6, 2012
Abstract
In this paper we study conditional distributions of independent, but not identically distributed Bernoulli random variables. The conditioning variable is the sum of the Bernoulli variables. We obtain Edgeworth expansions for the conditional expectations and the conditional variances and covariances. The results are of basic interest for several applications, e.g. for the study of conditional maximum likelihood estimation in Rasch models with many item parameters.
Published Online: 2012-11-06
Published in Print: 2012-11
© by Oldenbourg Wissenschaftsverlag, München, Germany
You are currently not able to access this content.
You are currently not able to access this content.
Articles in the same Issue
- Minimum VaR and minimum CVaR optimal portfolios: Estimators, confidence regions, and tests
- The covariance structure of cml-estimates in the Rasch model
- Asymptotic expansions for conditional moments of Bernoulli trials
- Erratum to: Dependence properties of dynamic credit risk models
Keywords for this article
Edgeworth expansions;
conditional expectations;
Bernoulli trials
Articles in the same Issue
- Minimum VaR and minimum CVaR optimal portfolios: Estimators, confidence regions, and tests
- The covariance structure of cml-estimates in the Rasch model
- Asymptotic expansions for conditional moments of Bernoulli trials
- Erratum to: Dependence properties of dynamic credit risk models