Zobrazeno 1 - 10
of 173
pro vyhledávání: '"Shanti S. Gupta"'
Autor:
Shanti S. Gupta, Jianjun Li
Publikováno v:
Journal of Statistical Planning and Inference. 136:2352-2366
This paper studies monotone empirical Bayes tests (MEBTs) for N ( θ , 1 ) under a linear loss. The purpose is to give a complete answer to an open problem raised by Karunamuni [1996. Optimal rates of convergence of empirical Bayes tests for the cont
Publikováno v:
Journal of Statistical Planning and Inference. 131:101-115
The convergence rates of empirical Bayes estimation in the exponential family are studied in this paper. We first develop an approach for obtaining the lower bound of empirical Bayes estimators. As an application of the approach, we demonstrate that
Autor:
Jianjun Li, Shanti S. Gupta
Publikováno v:
Journal of Statistical Planning and Inference. 129:3-18
This paper deals with the problem of selecting good populations with respect to a control from k ( ⩾ 2 ) populations. The random variable associated with population π i is assumed to be positive-valued and has density of form f ( x i | θ i ) = c
Autor:
Jianjun Li, Shanti S. Gupta
Publikováno v:
Statistics & Probability Letters. 65:177-185
In this paper, we consider the one-sided testing problem for lower truncation parameters through the empirical Bayes approach. The optimal rate of the monotone empirical Bayes tests is obtained and a test δ n achieving the optimal rate is constructe
Publikováno v:
Journal of Statistical Planning and Inference. 110:11-21
We investigate the problem of selecting the best population from positive exponential family distributions based on type-I censored data. A Bayes rule is derived and a monotone property of the Bayes selection rule is obtained. Following that property
Autor:
Shanti S. Gupta, Klaus J. Miescke
Publikováno v:
Journal of Statistical Planning and Inference. 103:101-115
From k normal populations N(θ1,σ12),…,N(θk,σk2), where the means θ 1 ,…,θ k ∈ R are unknown, and the variances σ12,…,σk2>0 are known, independent random samples of sizes n1,…,nk, respectively, are drawn. Based on these observations,
Autor:
Shanti S. Gupta, TaChen Liang
Publikováno v:
Journal of Statistical Planning and Inference. 103:191-203
We study the problem of selecting the most reliable Poisson population from among k competitors provided it is better than a control using the nonparametric empirical Bayes approach. An empirical Bayes selection procedure is constructed based on the
Autor:
Shanti S. Gupta
Publikováno v:
Encyclopedia of Statistical Sciences
This paper describes several optimal sampling problems that arise in connection with selection and ranking procedures. A selection procedure typically consists of three ingredients: (1) a sampling rule, (2) a stopping rule, and (3) a decision rule, t
Autor:
Shanti S. Gupta, TaChen Liang
Publikováno v:
Journal of Statistical Planning and Inference. 77:73-88
In this paper, we derive statistical selection procedures to partition k normal populations into ‘good’ or ‘bad’ ones, respectively, using the nonparametric empirical Bayes approach. The relative regret risk of a selection procedure is used a
Autor:
Shanti S. Gupta, James O. Berger
The Fifth Purdue International Symposium on Statistical Decision The was held at Purdue University during the period of ory and Related Topics June 14-19,1992. The symposium brought together many prominent leaders and younger researchers in statist