Closed sequential procedures for selecting the multinomial events which have the largest probabilities

Single-stage and closed sequential procedures for selecting the multinomial events which have the largest probabilities areconsidered. Two goals, Goal I (Selecting the s best categories without regard to order) and Goal II (Selecting the s best categories with regard to order) are studied in detail; here k ≥ 2 is the number of categories in the multjinomial distribution. Goal I includes as special cases, the goals of Bechhofer, Elmaghraby and Morse (1959) and Alam and Thompson (1972) which correspond here to the cases s = 1 and s = k-l, respectively; both foregoing articles gave single-stage procedures whi ch when used with an appropri ate si ng1e-stage slamp1e size n guarantee a probability requirement which employs the Isocalled indifference-zone approach. The sequenti a1 procedures tha t we propose achi eve the same probability of a correct selection as do the corresponding silngle stage procedures, uniformly in the unknown event probabilities . Moreover, this is accomplished with a smaller expected nu...

[1]  M. L. Eaton Some Optimum Properties of Ranking Procedures , 1967 .

[2]  K. Alam,et al.  On Selecting the Least Probable Multinomial Event , 1972 .

[3]  R. Bechhofer A Single-Sample Multiple Decision Procedure for Ranking Means of Normal Populations with known Variances , 1954 .

[4]  S. Elmaghraby,et al.  A Single-Sample Multiple-Decision Procedure for Selecting the Multinomial Event Which Has the Highest Probability , 1959 .

[5]  J. T. Ramey,et al.  A Sequential Procedure for Selecting the Most Probable Multinomial Event , 1979 .

[6]  A sequential sampling rule for selecting the most probable multinomial event , 1971 .

[7]  Harry Kesten,et al.  A PROPERTY OF THE MULTINOMIAL DISTRIBUTION , 1959 .

[8]  E. Lehmann On a Theorem of Bahadur and Goodman , 1966 .

[9]  J. T. Ramey,et al.  A bayes sequential procesure for selecting the most probable multinomial event , 1980 .

[10]  I. Olkin,et al.  Integral expressions for tail probabilities of the multinomial and negative multinomial distributions , 1965 .

[11]  M. Sobel THE DIRICHLET-TYPE 1 INTEGRAL AND ITS APPLICATIONS TO MULTINOMIAL-RELATED PROBLEMS , 1977 .

[12]  Edward J. Dudewicz,et al.  Further light on nonparametric selection efficiency , 1973 .

[13]  Bruce Levin,et al.  A Representation for Multinomial Cumulative Distribution Functions , 1981 .

[14]  Christopher Jennison Equal probability of correct selection for bernoulli selection procedures , 1983 .

[15]  F. Hwang,et al.  A class of selection problems for which more sampling is more informative , 1982 .

[16]  Robert E. Bechhofer,et al.  Sequential Identification and Ranking Procedures. , 1968 .

[17]  I. Olkin,et al.  Baseball Competitions—Are Enough Games Played? , 1978 .

[18]  Khursheed Alam,et al.  On Selecting the Most Probable Category , 1971 .

[19]  H. Robbins,et al.  Selecting the highest probability in binomial or multinomial trials. , 1981, Proceedings of the National Academy of Sciences of the United States of America.

[20]  On the performance characteristics of a closed adaptive sequential procedure for selecting the best bernoulli population , 1983 .

[21]  Ingram Olkin,et al.  Monotonicity properties of Dirichlet integrals with applications to the multinomial distribution and the analysis of variance , 1972 .

[22]  Edward J. Dudewicz,et al.  A Nonparametric Selection Procedure's Efficiency: Largest Location Parameter Case , 1971 .