research
∙
08/18/2023
Minimaxity under half-Cauchy type priors
This is a follow-up paper of Polson and Scott (2012, Bayesian Analysis),...
share
research
∙
07/24/2023
Information Geometry of Wasserstein Statistics on Shapes and Affine Deformations
Information geometry and Wasserstein geometry are two main structures in...
research
∙
06/07/2023
Modelling the discretization error of initial value problems using the Wishart distribution
This paper presents a new discretization error quantification method for...
research
∙
05/15/2023
Matrix quadratic risk of orthogonally invariant estimators for a normal mean matrix
In estimation of a normal mean matrix under the matrix quadratic loss, w...
research
∙
11/17/2022
Inadmissibility of the corrected Akaike information criterion
For the multivariate linear regression model with unknown covariance, th...
research
∙
07/05/2022
Asymptotic Analysis of Parameter Estimation for Ewens–Pitman Partition
We discuss the asymptotic analysis of parameter estimation for Ewens–Pit...
research
∙
05/27/2022
Adapting to arbitrary quadratic loss via singular value shrinkage
The Gaussian sequence model is a canonical model in nonparametric estima...
research
∙
08/30/2021
Generalized nearly isotonic regression
The problem of estimating a piecewise monotone sequence of normal means ...
research
∙
03/01/2021
Interpretable Stein Goodness-of-fit Tests on Riemannian Manifolds
In many applications, we encounter data on Riemannian manifolds such as ...
research
∙
07/21/2020
Wasserstein Statistics in One-dimensional Location-Scale Model
Wasserstein geometry and information geometry are two important structur...
research
∙
05/26/2020
Matrix superharmonic priors for Bayes estimation under matrix quadratic loss
We investigate Bayes estimation of a normal mean matrix under the matrix...
research
∙
04/30/2020
Information geometry of operator scaling
Matrix scaling is a classical problem with a wide range of applications....
research
∙
03/22/2020
Generalization of partitioned Runge–Kutta methods for adjoint systems
This study computes the gradient of a function of numerical solutions of...
research
∙
02/17/2020
A Stein Goodness-of-fit Test for Directional Distributions
In many fields, data appears in the form of direction (unit vector) and ...
research
∙
10/15/2019
Adjoint-based exact Hessian-vector multiplication using symplectic Runge–Kutta methods
We consider a function of the numerical solution of an initial value pro...
research
∙
07/24/2019
Estimation of ordinary differential equation models with discretization error quantification
We consider estimation of ordinary differential equation (ODE) models fr...
research
∙
05/15/2019
Information criteria for non-normalized models
Many statistical models are given in the form of non-normalized densitie...
research
∙
04/05/2019
Predictive density estimation under the Wasserstein loss
We investigate predictive density estimation under the L^2 Wasserstein l...
research
∙
03/08/2019
Imputation estimators for unnormalized models with missing data
We propose estimation methods for unnormalized models with missing data....
research
∙
01/23/2019
Unified estimation framework for unnormalized models with statistical efficiency
Parameter estimation of unnormalized models is a challenging problem bec...
research
∙
01/23/2019
Unified efficient estimation framework for unnormalized models
Parameter estimation of unnormalized models is a challenging problem bec...
research
∙
08/24/2018
Analysis of Noise Contrastive Estimation from the Perspective of Asymptotic Variance
There are many models, often called unnormalized models, whose normalizi...
research
∙
06/20/2018
Game-theoretic derivation of upper hedging prices of multivariate contingent claims and submodularity
We investigate upper and lower hedging prices of multivariate contingent...
research
∙
05/19/2018
Estimation of Non-Normalized Mixture Models and Clustering Using Deep Representation
We develop a general method for estimating a finite mixture of non-norma...
research
∙
06/05/2017