Distribution-free and model-free multivariate feature screening via multivariate rank distance correlation

A Distribution-Free Multivariate Control Chart

Monitoring multivariate quality variables or data streams remains an important and challenging problem in statistical process control (SPC). Although the multivariate SPC has been extensively studied in the literature, designing distribution-free control schemes are still challenging and yet to be addressed well. This paper develops a new nonparametric methodology for monitoring location parame...

Multivariate normal distribution - Wikipedia, the free encyclopedia

1 General case 1.1 Cumulative distribution function 1.2 A counterexample 1.3 Normally distributed and independent 2 Bivariate case 3 Affine transformation 4 Geometric interpretation 5 Correlations and independence 6 Higher moments 7 Conditional distributions 8 Fisher information matrix 9 Kullback-Leibler divergence 10 Estimation of parameters 11 Entropy 12 Multivariate normality tests 13 Drawin...

Screening for a Multivariate Mixture Normal Distribution

Feature Screening via Distance Correlation Learning.

This paper is concerned with screening features in ultrahigh dimensional data analysis, which has become increasingly important in diverse scientific fields. We develop a sure independence screening procedure based on the distance correlation (DC-SIS, for short). The DC-SIS can be implemented as easily as the sure independence screening procedure based on the Pearson correlation (SIS, for short...

Distribution Free Decomposition of Multivariate Data SPR'98 Invited submission

We present a practical approach to nonparametric cluster analysis of large data sets. The number of clusters and the cluster centers are automatically derived by mode seeking with the mean shift procedure on a reduced set of points randomly selected from the data. The cluster boundaries are delineated using a k-nearest neighbor technique. The proposed algorithm is stable and e cient, a 10000 po...