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
We present a double bootstrap procedure for reducing coverage error in confidence intervals of summary statistics for independent and identically distributed functional data.
We show that,in the functional data context,by appropriately exploiting the functional nature of the data,it is possible to cluster the observations asymptotically perfectly in the case of different l