Gaussian processes,together with an objective Bayesian implementation of the processes,have become a common tool for emulating(approximating)complex computer models.
Predictive performance in shrinkage regression suffers from two major difficulties:(ⅰ)the amount of relative shrinkage is monotone in the singular values of the design matrix and(ⅱ)the amount of shrin
In this talk,we provide bounds on the asymptotic variance for a class of sequential Monte Carlo(SMC)samplers designed for approximating multimodal distributions.
Time series regression has two purposes-comprehend the functional dependence of variable of interest on covariates and forecast the dependent variable for future values of covariates.
In big data analysis for detecting rare and weak signals among n features,the Higher Criticism test(HC),Berk-Jones test(B-J),and some (o) -divergence tests have been proven optimal under the asymptoti