21 citations · 31 across the 4 of their papers we have counts for
5 papers
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…
On Selection Criteria for the Tuning Parameter in Robust Divergence
Shonosuke Sugasawa, Shouto Yonekura
While robust divergence such as density power divergence and -divergence is helpful for robust statistical inference in the presence of outliers, the tuning parameter that contr…
Adaptation of the Tuning Parameter in General Bayesian Inference with Robust Divergence
Shouto Yonekura, Shonosuke Sugasawa
We introduce a methodology for robust Bayesian estimation with robust divergence (e.g., density power divergence or γ-divergence), indexed by a single tuning parameter. It is well…
Online Smoothing for Diffusion Processes Observed with Noise
Shouto Yonekura, Alexandros Beskos
We introduce a methodology for online estimation of smoothing expectations for a class of additive functionals, in the context of a rich family of diffusion processes (that may inc…
Asymptotic Analysis of Model Selection Criteria for General Hidden Markov Models
Shouto Yonekura, Alexandros Beskos, Sumeetpal S. Singh
The paper obtains analytical results for the asymptotic properties of Model Selection Criteria -- widely used in practice -- for a general family of hidden Markov models (HMMs), th…