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math.ST2018
Minimax Predictive Density for Sparse Count Data
Keisuke Yano, Ryoya Kaneko, Fumiyasu Komaki
This paper discusses predictive densities under the Kullback--Leibler loss for high-dimensional Poisson sequence models under sparsity constraints. Sparsity in count data implies z…
math.ST2018
On frequentist coverage errors of Bayesian credible sets in moderately high dimensions
Keisuke Yano, Kengo Kato
In this paper, we study frequentist coverage errors of Bayesian credible sets for an approximately linear regression model with (moderately) high dimensional regressors, where the…
math.ST2017
On -Admissibility in High Dimension and Nonparametrics
Keisuke Yano, Fumiyasu Komaki
In this paper, we discuss the use of -admissibility for estimation in high-dimensional and nonparametric statistical models. The minimax rate of convergence is widely…