Count responses with structural zeros are very common in medical and psychosocial research,especially in alcohol and HIV research,and the zero-inflated Poisson(ZIP)and zero-inflated negative binomial
Most existing binary classification methods target on the optimization of the overall classification risk and may fail to serve some real-world applications such as cancer diagnosis,where users are mo
We study the asymptotic results of linear discriminant analysis(LDA)in large dimensional data where the observation dimension p,is of the same order of magnitude as the sample size n.
The major goals of metagenomics are to identify and study the entire collection of microbial species in a set of targeted samples through sequencing bulk DNA extracted directly from the samples.
The parametric methods,such as autoregressive models or latent growth modeling are usually inflexible to model the dependence and nonlinear effects among the changes of latent traits whenever the time
We develop a novel method called SParse Optimal Transformations(SPOT)to simultaneously select important variables and explore relationships between the response and predictor variables in high dimensi
This paper develops three Bayesian case influence measures including the -divergence,Cooks posterior mode distance and Cooks posterior mean distance to identify influential observations,and a Bayesia
We propose a semiparametric inference approach for the proportional mean residual life model with right-censored length-biased data,which arise frequently in observational studies,espe-cially in epide
Missing data cause challenging issues,particularly in Phase Ⅲ registration trials,as highlighted by the European Medicines Agency(EMA)and the US National Research Council(NRC)..We explore,as a case st