Gene selection is an important issue in analyzing multiclass microarray data. Among many proposed selection methods, the traditional ANOVA F test statistic has been employed to identify informative genes for both class prediction (classification) and discovery problems. However, the F test statistic assumes an equal variance. This assumption may not be realistic for gene expression data. This p...

This paper establishes monotonicity of the chi-square test statistic. As the more efficient parameter estimator is plugged into the test statistic, the degrees of freedom of the resulting chi-square test statistic monotonically increase.

The paper presents new strategies for testing and rating the relevance of rules in the Fuzzy{ROSA (Rule Oriented Statistic Analysis) method for data based rule generation. Speciic characteristics and diierences between the proposed strategies are pointed out.

The paper presents new strategies for testing and rating the relevance of rules in the Fuzzy{ROSA (Rule Oriented Statistic Analysis) method for data based rule generation. Speciic characteristics and diierences between the proposed strategies are pointed out.

We consider the problem of testing a statistical hypothesis where the scientifically meaningful test statistic is a function of latent variables. In particular , we consider detection of genetic linkage, where the latent variables are patterns of inheritance at specific genome locations. Fuzzy p-values, introduced by Geyer & Meeden (2005) are random variables (described by their probability dis...