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Asymptotic expansions for conditional moments of Bernoulli trials
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Helmut Strasser
Veröffentlicht/Copyright:
6. November 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
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- 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
Artikel in diesem Heft
- 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
