This paper describes a threshold classification with <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$K$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi>K</mi> </math> </EquationSource> </InlineEquation> populations whose membership category is associated with the threshold process of a latent variable. It is seen that the optimal procedure (Bayes procedure) for the classification involves a nonlinear classification rule and...</equationsource></equationsource></inlineequation>

Simultaneous estimation in nonlinear multivariate regression contexts is a complex problem in inference. In this paper, we compare the methodology suggested in the literature for an unknown covariance matrix among response components, the methodology by Beauchamp and Cornell (B&C), with the...

The L <Subscript>1</Subscript>-median is a robust estimator of multivariate location with good statistical properties. Several algorithms for computing the L <Subscript>1</Subscript>-median are available. Problem specific algorithms can be used, but also general optimization routines. The aim is to compare different algorithms with respect...</subscript></subscript>

Classification of samples into two or multi-classes is to interest of scientists in almost every field. Traditional statistical methodology for classification does not work well when there are more variables (p) than there are samples (n) and it is highly sensitive to outlying observations. In...