6 papers
Optimal dimension growth rates in the high dimensional Central Limit Theorems
Mayukh Choudhury, Debraj Das
We investigate the optimal dimension growth rates for the high-dimensional Central Limit Theorem (CLT) over half spaces, Euclidean balls and Borel convex sets, under the existence…
Fast high-dimensional mean testing via logistic regression
Sayan Das, Debraj Das, Subhajit Dutta
We propose computationally efficient tests for equality of mean vectors of two or more high-dimensional populations. Central to our approach is an equivalence between equality of m…
Asymptotic Theory of Tail Dependence and Bootstrap for Checkerboard Copulas
Mayukh Choudhury, Debraj Das, Sujit Ghosh
A comprehensive asymptotic and bootstrap theory is established for checkerboard-based estimation of the copula and its lower and upper tail copula counterparts under unknown margin…
High Dimensional Gaussian and Bootstrap Approximations in Generalized Linear Models
Mayukh Choudhury, Debraj Das
Generalized Linear Model (or GLM) extends the ordinary linear regression by linking the mean of the response variable to covariates through appropriate link functions. GLM is widel…
Asymptotic Theory of -fold Cross-validation in Lasso and the validity of Bootstrap
Mayukh Choudhury, Debraj Das
Least absolute shrinkage and selection operator or Lasso is one of the widely used regularization methods in regression. Statisticians usually implement Lasso in practice by choosi…
Bootstrapping Lasso in Generalized Linear Models
Mayukh Choudhury, Debraj Das
Generalized linear model or GLM constitutes a large class of models and essentially extends the ordinary linear regression by connecting the mean of the response variable with the…