Closed sequential procedures for selecting the multinomial events which have the largest probabilities
DOI10.1080/03610928408828875zbMath0571.62069OpenAlexW2009953196MaRDI QIDQ3687545
Radhika V. Kulkarni, Robert E. Bechhofer
Publication date: 1984
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://hdl.handle.net/1813/8500
tablesmultinomial distributionexpected sample sizeprobability of correct selectionranking procedurescurtailed sequential procedureclosed procedureslargest probabilitiessingle-stage procedures
Sampling theory, sample surveys (62D05) Sequential statistical analysis (62L10) Statistical ranking and selection procedures (62F07)
Related Items (9)
Cites Work
- Unnamed Item
- A representation for multinomial cumulative distribution functions
- A sequential sampling rule for selecting the most probable multinomial event
- Equal probability of correct selection for bernoulli selection procedures
- On the performance characteristics of a closed adaptive sequential procedure for selecting the best bernoulli population
- A bayes sequential procesure for selecting the most probable multinomial event
- Further light on nonparametric selection efficiency
- Integral expressions for tail probabilities of the multinomial and negative multinomial distributions
- On a Theorem of Bahadur and Goodman
- Some Optimum Properties of Ranking Procedures
- Monotonicity Properties of the Multinomial Distribution
- A Property of the Multinomial Distribution
- A Single-Sample Multiple-Decision Procedure for Selecting the Multinomial Event Which Has the Highest Probability
- Monotonicity properties of Dirichlet integrals with applications to the multinomial distribution and the analysis of variance
- On Selecting the Least Probable Multinomial Event
- A Single-Sample Multiple Decision Procedure for Ranking Means of Normal Populations with known Variances
This page was built for publication: Closed sequential procedures for selecting the multinomial events which have the largest probabilities