This report deals with procedures for random-size subset selection from k(> 2) given populations where the distribution of ir^(i = l, ..., k) has a density f^(x;0^). Let ••• -®[k] denote unknown values of the parameters, and let ^[i]» ***'ïï[k] denote the corresponding populations. First, we have considered the problem of selection for consider the /s procedure that selects TT. if sup L(0;x) > ...

For applications in texture synthesis, we derive two approximate Bayes criteria for selecting a model from a collection of Markov random fields. The first criterion is based on a penalized maximum likelihood. The second criterion, a Markov chain Monte Carlo approximation to the first, has distinct computational advantages. Some simulation results are also presented.

When the DGP is nested in the model, PcGets delivers high performance selection across different (unknown) states of nature. One of its steps involves sub-sample post-selection assessment, and here we consider its properties and investigate its practical application. The simulation results show that conditional on retaining a variable, sub-sample information cannot discriminate between substant...

Nonlinear system identi cation involves selecting the order of the given model based on the input-output data. A bootstrap model selection procedure which selects the model by minimising bootstrap estimates of the prediction error is developed. Bootstrap based model selection procedures are attractive because the bootstrap observations generated for the model selection can also be used in subse...

A linear utility model is introduced for optimal selection when several subpopulations of applicants are to be distinguished. Using this model, procedures are described for obtaining optimal cutting scores in subpopulations in quota-free as well as quota-restricted selection situations. The cutting scores are optimal in the sense that they maximize the overall expected utility of the selection ...

Indifference-zone-selection procedures have been widely studied and applied to determine the required sample sizes for selecting a good design from k alternatives. However, efficiency is still a key concern for application of simulation to ranking and selection problems. In this paper, we present a new approach that can further enhance the efficiency of indifferencezone-selection procedures. Ou...

We propose a new selection procedures in unequal probability sampling that can be used with Horvitz and Thompson Estimator. Expression for inclusion probability for ith unit ( i  ) and joint inclusion probability of ith and jth unit ( ij  ) has been obtained. Some desirable properties of i  and ij  has been verified for proposed procedure.

To compare several promising product designs, manufacturers must measure their performance under multiple environmental conditions. In many applications, a product design is considered to be seriously flawed if its performance is poor under any level of the environmental factor. For example, if a particular automobile battery design does not function well under some temperature conditions, then...

August 2000 Abstract: In a presentation to the American Economics Association, McCloskey (1998) argued that "statistical significance is bankrupt" and that economists' time would be "better spent on finding out How Big Is Big". This brief survey is devoted to methods of determining "How Big Is Big". It is concerned with a rich body of literature called selection procedures, which are statistica...

Little is known about the ability of incentives to influence decisions by physicians regarding choices of settings for care delivery. In the context of outpatient procedural care, the emergence of freestanding ambulatory surgery centers (ASCs) as alternatives to hospital-based outpatient departments (HOPDs) creates a unique opportunity to study this question. We advance a model where physicians...