New Bayesian method improves accuracy of probability density estimation on [0,1]
The article explores better ways to estimate probability densities on the unit interval [0,1]. By using a Bayesian framework, the researchers found that choosing the right bandwidth and kernel function can improve density estimation. In simulations, the Bayesian bandwidth estimator outperformed others, and the choice of kernel function affected the accuracy of the estimates. The study shows that the proposed methods can enhance how probability densities on [0,1] are currently estimated.
