Biomedical Engineering and Bioengineering Commons^™

A Balanced Approach To Adaptive Probability Density Estimation, Julio Kovacs, Cailee Helmick, Willy Wriggers

Mechanical & Aerospace Engineering Faculty Publications

Our development of a Fast (Mutual) Information Matching (FIM) of molecular dynamics time series data led us to the general problem of how to accurately estimate the probability density function of a random variable, especially in cases of very uneven samples. Here, we propose a novel Balanced Adaptive Density Estimation (BADE) method that effectively optimizes the amount of smoothing at each point. To do this, BADE relies on an efficient nearest-neighbor search which results in good scaling for large data sizes. Our tests on simulated data show that BADE exhibits equal or better accuracy than existing methods, and visual tests …