It has long been known that for the comparison of pairwise nested models, a decision based on the Bayes factor produces a consistent model selector (in the frequentist sense). Here we go beyond the ∗Distinguished Professor, Department of Statistics, University of Florida, Gainesville, FL 32611. Supported by National Science Foundation Grant DMS-04-05543. Email: [email protected]. †Professor,...

Fully sequential selection procedures have been developed in the field of stochastic simulation to find the simulated system with the best expected performance when the number of alternatives is finite. Kim and Nelson proposed the KN procedure to allow for unknown and unequal variances and the use of common random numbers. KN approximates the raw sum of differences between observations from two...

The emergence of sustainability paradigm has influenced many research disciplines including supply chain management. It has drawn the attention of manufacturing companies’ CEOs to incorporate sustainability in their supply chain and manufacturing activities. Supplier selection problem, as one of the main problems in supply chain activities, is also combined with sustainable development where tr...

Nine generations of selection for high ovulation rate were followed by two generations of random selection and then eight generations of selection for increased litter size at birth, decreased age at puberty, or continued random selection in the high ovulation rate line. A control line was maintained with random selection. Line means were regressed on generation number and on cumulative selecti...

The behaviour of model selection procedures based on diierent criteria such as cross-validation is investigated in a simulation study. Emphasis is on the relationship to the problem of estimating the prediction quality of a model.

The problem of constructing classification methods based on both classified and unclassified data sets is considered for analyzing data with complex structures. We introduce a semi-supervised logistic discriminant model with Gaussian basis expansions. Unknown parameters included in the logistic model are estimated by regularization method along with the technique of EM algorithm. For selection ...

This note shows how to use the GMM model and moment selection procedures of Andrews and Lu (2001) for the purpose of detection of a general structural break in a dynamic panel data model. It compares the resulting method with the classical hypothesis testing approach of De Wachter and Tzavalis (2004). Out of 3 model selection criteria studied, the GMMHQIC criterion is found to perform most simi...

behaviour of the dilution characteristics of the coastal waters off tuticorin is presented in thebackground of setting up of a desalination plant. simulations of dispersion and spreading of the proposeddischarges has been carried out. scenarios of dilutions were assessed based on the results of a 2d model using the advection-dispersion theory. it is observed that under prevailing currents in th...

The purpose of this paper is to explain the interest and importance of (approximate) models and model selection in Statistics. Starting from the very elementary example of histograms we present a general notion of finite dimensional model for statistical estimation and we explain what type of risk bounds can be expected from the use of one such model. We then give the performance of suitable mo...

To compute norms from reference group test scores, continuous norming is preferred over traditional norming. A suitable continuous norming approach for continuous data is the use of the Box-Cox Power Exponential model, which is found in the generalized additive models for location, scale, and shape. Applying the Box-Cox Power Exponential model for test norming requires model selection, but it i...