3 papers
stat.ME2026
A New Approach to Goodness of Fit for Ergodic Markov Processes
Vance Martin, Yoshihiko Nishiyama, John Stachurski +1
We introduce a new density-based goodness of fit test for ergodic Markov processes. Our test compares the data against the class of models specified in the null hypothesis, and rej…
stat.ME2022
Fully Data-driven Normalized and Exponentiated Kernel Density Estimator with Hyvärinen Score
Shunsuke Imai, Takuya Koriyama, Shouto Yonekura +2
We introduce a new deal of kernel density estimation using an exponentiated form of kernel density estimators. The density estimator has two hyperparameters flexibly controlling th…
math.ST2022
Higher-Order Asymptotic Properties of Kernel Density Estimator with Global Plug-In and Its Accompanying Pilot Bandwidth
Shunsuke Imai, Yoshihiko Nishiyama
This study investigates the effect of bandwidth selection via a plug-in method on the asymptotic structure of the nonparametric kernel density estimator. We generalise the result o…