2 citations · 7 across the 12 of their papers we have counts for
5 papers · 1 filter
Wasserstein Statistics in One-dimensional Location-Scale Model
Shun-ichi Amari, Takeru Matsuda
Wasserstein geometry and information geometry are two important structures to be introduced in a manifold of probability distributions. Wasserstein geometry is defined by using the…
Estimation under matrix quadratic loss and matrix superharmonicity
Takeru Matsuda, William E. Strawderman
We investigate estimation of a normal mean matrix under the matrix quadratic loss. Improved estimation under the matrix quadratic loss implies improved estimation of any linear com…
Information geometry of operator scaling
Takeru Matsuda, Tasuku Soma
Matrix scaling is a classical problem with a wide range of applications. It is known that the Sinkhorn algorithm for matrix scaling is interpreted as alternating e-projections from…
Generalization of partitioned Runge--Kutta methods for adjoint systems
Takeru Matsuda, Yuto Miyatake
This study computes the gradient of a function of numerical solutions of ordinary differential equations (ODEs) with respect to the initial condition. The adjoint method computes t…
A Stein Goodness-of-fit Test for Directional Distributions
Wenkai Xu, Takeru Matsuda
In many fields, data appears in the form of direction (unit vector) and usual statistical procedures are not applicable to such directional data. In this study, we propose non-para…