排序方式: 共有52条查询结果,搜索用时 15 毫秒
1.
Explicit expressions for Bayes invariant quadratic estimates, biased and unbiased, are presented and proved to cover the entire class of admissible estimates in the considered classes. An unbalanced genetic model is studied for demonstration. 相似文献
2.
Tiebreak rules are necessary for revealing indifference in non- sequential decisions. I focus on a preference relation that satisfies Ordering and fails Independence in the following way. Lotteries a and b are indifferent but the compound lottery 0.5f, 0.5b is strictly preferred to the compound lottery 0.5f, 0.5a. Using tiebreak rules the following is shown here: In sequential decisions when backward induction is applied, a preference like the one just described must alter the preference relation between a and b at certain choice nodes, i.e., indifference between a and b is not stable. Using this result, I answer a question posed by Rabinowicz (1997) concerning admissibility in sequential decisions when indifferent options are substituted at choice nodes. 相似文献
3.
Peter Thompson 《统计学通讯:理论与方法》2013,42(3):537-553
The admissibility of testing procedures is examined when the loss function used is an increasing function of the p-value rather than the standard 0–1 loss. It is shown that the class of admissible procedures using the new approach is a subset of the class of admissible procedures using the 0–1 loss. 相似文献
4.
Malwane M. A. Ananda 《统计学通讯:理论与方法》2013,42(11):3219-3227
The problem of estimating the one parameter exponential reliability function for a system composed of l componentes in series is considered. Under the type II censoring scheme, the Bayes nature of the minimum variance unbiased estimator is demonstrated and the admissibility of related generalized Bayes estimators is established. For the one component case, the best unbiased estimator is admissible. 相似文献
5.
S. Sengupta 《统计学通讯:理论与方法》2013,42(19):5745-5750
ABSTRACTLet P be the proportion of individuals in a finite population possessing a sensitive attribute. We consider the problem of unbiased estimation of (i) the variance of a linear unbiased estimator of P and (ii) the population variance P (1—P) for a given probability sampling design under Warner's (1965) randomized response (RR) plan when independent responses are obtained from each sampled individual as many times as he/she is selected in the sample and prove the admissibility of a quadratic unbiased estimator for each. 相似文献
6.
Tapan K. Nayak 《统计学通讯:理论与方法》2013,42(9):2039-2056
Based on a capture-recapture sample of size $i;n+k,n≥ l,k ≥ 0, from a population of an unknown number of distinct species (or classes), the problem of estimating the total probability of the species unobserved in the first n selections is considered. As the estimand depends on both the unknown parameters and the data, the standard theory of estimation is inadequate for this problem A suitable definition of sufficiency is introduced and used to prove a Rao-Blackwell type result and discuss uniformly minimum mean squared error unbiased estimation. An alternative proof for an inadmissibility result is presented. The new proof gives more insight and a method for deriving improved estimators. The theoretical developments may be useful in other problems concerning inferences about random parametric functions. 相似文献
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8.
This paper addresses the problem of estimating a matrix of the normal means, where the variances are unknown but common. The approach to this problem is provided by a hierarchical Bayes modeling for which the first stage prior for the means is matrix-variate normal distribution with mean zero matrix and a covariance structure and the second stage prior for the covariance is similar to Jeffreys’ rule. The resulting hierarchical Bayes estimators relative to the quadratic loss function belong to a class of matricial shrinkage estimators. Certain conditions are obtained for admissibility and minimaxity of the hierarchical Bayes estimators. 相似文献
9.
This paper considers estimation of a exponential mean time to failure using a loss function that reflects both goodness of
fit and precision of estimation. The admissibility and inadmissibility of a class of linear estimators of the form
are studied. 相似文献
10.
Let Π1,…,Πk be k populations with Πi being Pareto with unknown scale parameter αi and known shape parameter βi;i=1,…,k. Suppose independent random samples (Xi1,…,Xin), i=1,…,k of equal size are drawn from each of k populations and let Xi denote the smallest observation of the ith sample. The population corresponding to the largest Xi is selected. We consider the problem of estimating the scale parameter of the selected population and obtain the uniformly minimum variance unbiased estimator (UMVUE) when the shape parameters are assumed to be equal. An admissible class of linear estimators is derived. Further, a general inadmissibility result for the scale equivariant estimators is proved. 相似文献