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A new nonparametric density ratio estimator using the beta kernel is proposed. It is shown that the beta kernel density ratio estimator (KDRE) is free of boundary or tail bias,… Click to show full abstract
A new nonparametric density ratio estimator using the beta kernel is proposed. It is shown that the beta kernel density ratio estimator (KDRE) is free of boundary or tail bias, and the asymptotic properties of the beta KDRE are derived. Simulation studies are conducted to illustrate the finite sample performance of the beta KDRE.
Keywords:
density ratio;
using beta;
beta kernel;
nonparametric direct
Journal Title: Statistics
Year Published: 2020
Link to full text (if available)
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Journal Title: Statistics
Year Published: 2020
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!