Change-point detection is an integral component of statistical modeling and estimation.For high-dimensional data,classical methods based on the Mahalanobis distance are typically in-applicable.
Array-based CGH experiments are designed to detect genomic aberrations or regions of DNA copy-number variation that are associated with an outcome,typically a state of disease.
The identification of genes determining spatial-temporal changes of ecological interactions is of paramount importance for ecological and evolutionary research.
Some existing confidence interval methods and hypothesis testing methods in the analysis of a contingency table with incomplete observations in both margins entirely depend on an underlying assumption
Although complete randomization ensures covariate balance on average,the chance for observing significant differences between treatment and control covariate distributions is high especially with many