The main purpose of microarray studies is screening to identify differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing or ranking genes is a relevant statistical task in microarray studies. In this article, we develop 3 empirical Bayes methods for gene ranking on the basis of differential expression, using hierarchical mi...

Nonparametric discriminant analysis methods are considered to segment brain multispectral MR images. Methods are based on i) a nonparametric estimate of voxel density functions by Kernel regression; ii) possibly a transform of the multispectral voxels into principal or independent components; iii) a classic Bayes 0-1 classification rule. Experiments are shown based on synthetic (brainweb) and r...

in a finite stationary markov chain, transition probabilities may depend on some explanatoryvariables. a similar problem has been considered here. the corresponding posteriors are derived andinferences are done using these posteriors. finally, the procedure is illustrated with a real example.

the problem of estimating the parameter ?, when it is restricted to an interval of the form , in a class of discrete distributions, including binomial negative binomial discrete weibull and etc., is considered. we give necessary and sufficient conditions for which the bayes estimator of with respect to a two points boundary supported prior is minimax under squared log error loss function. for s...

in this research, an iterative approach is employed to recognize and classify control chart patterns. to do this, by taking new observations on the quality characteristic under consideration, the maximum likelihood estimator of pattern parameters is first obtained and then the probability of each pattern is determined. then using bayes’ rule, probabilities are updated recursively. finally, when...

In standard notation, let {H1,H2, · · · ,Hm} and {A1, A2, · · · , An} be two distinct partitions of the sample space, or equivalently two sets of events satisfying three properties: (i) each event is non-void, (ii) events in the same set are mutually exclusive (i.e. P (Hj ∪Hk) = P (Hj)+P (Hk) for j 6= k), and (iii) each set is collectively exhaustive, (i.e. P (∪i=1Hj) = 1). The Bayes formula in...

In this paper, by considering an $$M|M|1|\infty$$ queueing model, Bayes estimators of traffic intensity and system performance measures are discussed under (i) squared error loss function (SELF) (ii) entropy (ELF) (iii) LINEX with Beta prior. Further, minimum posterior risk associated obtained SELF. The the model compared Uniformly Minimum Variance Unbiased Estimators (UMVUEs) through simulation.