Recent developments in high-throughput sequencing technologies have made it possible to search for both rare and common genetic variants associated with complex diseases.
Principal component analysis(PCA)has been a prominent tool for high-dimensional data analysis.Online algorithms that estimate the principal component by processing streaming data are of tremendous pra
Variance estimation presents challenges in the context of complex survey designs.Conventional variance estimators rely on second-order inclusion probabilities that can be difficult to compute for some
In logistic regression,separation occurs when a linear combination of the predictors can perfectly classify part or all of the observations in the sample,and as a result,finite maximum likelihood esti
The most popular method to model the relationship between the scalar response and the functional predictor is the functional linear model because of its simplicity and easy interpretation.
Assume a common change may occur in a portion of N independent panels and each panel consists of a sequence of independent random variables following a standard exponential family distribution.
Gene set enrichment analyses(GSEA)are powerful inferential methods widely used in genomic research to identify significant gene sets,such as Gene Ontology terms and molecular pathways.
For sequences of random backward nested subspaces as occur,say,in dimension reduction for manifold or stratified space valued data,asymptotic results are derived.
In ultrahigh dimensional data analysis,variable screening has been routinely per-formed before tting complex models with the goal to e ciently reduce data dimension while still keeping majority of th