This paper addresses the deconvolution problem of estimating a
square-in...
We introduce an original method of multidimensional ridge penalization i...
Functional principal components analysis is a popular tool for inference...
In this paper, we develop uniform inference methods for the conditional ...
Suppose there are two unknown parameters, each parameter is the solution...
Sample splitting is widely used in statistical applications, including
c...
Suppose we are using a generalized linear model to predict a scalar outc...
This paper develops a novel approach to density estimation on a network....
We present a new functional Bayes classifier that uses principal compone...
Distribution estimation for noisy data via density deconvolution is a
no...