Estimating Ordered Probabilities
About: This article is published in Annals of Mathematical Statistics. The article was published on 01 Sep 1963. and is currently open access. The article focuses on the topics: Huber loss & Half-normal distribution.
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Citations
Simultaneous estimation of ordered parameters
Somesh Kumar,Divakar Sharma +1 more
TL;DR: The problem of estimating ordered parameters is encountered in biological, agricultural, reliability and various other experiments as discussed by the authors, where the authors consider two populations with densities f1(x 1-ω1) and f2(x 2-ω2) where ω1#ω2.
38
Mixed estimators of two ordered exponential means
G. Vijayasree,Harshinder Singh +1 more
TL;DR: In this paper, a random sample of size ni was drawn from an exponential distribution with mean λi, i=1,2, satisfying λ1⩽λ2.
26
Simultaneous estimation of two ordered exponential parameters
G. Vijayasree,Harshinder Singh +1 more
TL;DR: In this paper, a mixed estimator of (λ 1, λ 2 ), λ 1 ≤ λ2 has been shown to outperform the usual estimator when the loss function is the sum of squared errors and a class of estimators admissible in the class of mixed estimators are found.
19
Estimation of the order restricted scale parameters for two populations from the Lomax distribution
TL;DR: It is proved that the best equivariant estimators of the scale parameters (in the unrestricted case) are not admissible and estimators that improve upon the usual ones are constructed (when these parameters are known to be ordered).
17
References
An empirical distribution function for sampling with incomplete information
TL;DR: In this article, it was shown that the consistency property of the maximum likelihood estimators depends on a grouping of observations which might very well appeal to an investigator on purely intuitive grounds.
On minimax statistical decision procedures and their admissibility
TL;DR: In this paper, the authors considered the problem of making a decision on the basis of a sequence of observations on a random variable and gave two loss functions, each depending on the distribution of the random variable, the number of observations taken, and the decision made.