An extension of principal component analysis called ipPCA has been proposed earlier for analyzing structure in genetic data. This non-parametric framework iteratively classifies ...
Background: The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used ...
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
Background: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various fa...
Abstract. A main focus of statistical shape analysis is the description of variability of a population of geometric objects. In this paper, we present work in progress towards mode...
Martin Styner, Kevin Gorczowski, P. Thomas Fletche...