This is a follow-up paper of Polson and Scott (2012, Bayesian Analysis),...
Information geometry and Wasserstein geometry are two main structures
in...
This paper presents a new discretization error quantification method for...
In estimation of a normal mean matrix under the matrix quadratic loss, w...
For the multivariate linear regression model with unknown covariance, th...
We discuss the asymptotic analysis of parameter estimation for Ewens–Pit...
The Gaussian sequence model is a canonical model in nonparametric estima...
The problem of estimating a piecewise monotone sequence of normal means ...
In many applications, we encounter data on Riemannian manifolds such as ...
Wasserstein geometry and information geometry are two important structur...
We investigate Bayes estimation of a normal mean matrix under the matrix...
Matrix scaling is a classical problem with a wide range of applications....
This study computes the gradient of a function of numerical solutions of...
In many fields, data appears in the form of direction (unit vector) and ...
We consider a function of the numerical solution of an initial value pro...
We consider estimation of ordinary differential equation (ODE) models fr...
Many statistical models are given in the form of non-normalized densitie...
We investigate predictive density estimation under the L^2 Wasserstein l...
We propose estimation methods for unnormalized models with missing data....
Parameter estimation of unnormalized models is a challenging problem bec...
Parameter estimation of unnormalized models is a challenging problem bec...
There are many models, often called unnormalized models, whose normalizi...
We investigate upper and lower hedging prices of multivariate contingent...
We develop a general method for estimating a finite mixture of non-norma...
We develop an empirical Bayes (EB) algorithm for the matrix completion
p...