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stat.ME2026
Sparse Variable Sharpening in High-Dimensional Kernel Density Estimation
Kiheiji Nishida
High-dimensional kernel density estimation suffers from the curse of dimensionality. This study proposes a hybrid density estimator defined as the product of a joint density over a…
stat.ME2022
Kernel Density Estimation by Genetic Algorithm
Kiheiji Nishida
This study proposes a data condensation method for multivariate kernel density estimation by genetic algorithm. First, our proposed algorithm generates multiple subsamples of a giv…
stat.ME2017★ 1 cited
Skewing Methods for Variance-Stabilizing Local Linear Regression Estimation
Kiheiji Nishida
It is well-known that kernel regression estimators do not produce a constant estimator variance over a domain. To correct this problem, Nishida and Kanazawa (2015) proposed a varia…