Density estimation is a fundamental component in statistical analysis, aiming to infer the probability distribution of a random variable from a finite sample without imposing restrictive parametric ...

© CBS Density estimation of complex data processes by means of neural networks and the integration of these networks in filter methods for the analysis of time ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

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We propose a method for reconstructing a probability density function (pdf) from a sample of an n-dimensional probability distribution. The method works by iteratively applying some simple ...

Continuity or discontinuity of probability density functions of data often plays a fundamental role in empirical economic analysis. For example, for identification and inference of causal effects in ...

We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using ...

Vol. 46, No. 4, Climate Adaptation Actions Machine Learning for Camera Traps Crippling Loss in Waterfowl (September 2022), pp. 1-14 (14 pages) American black bears (Ursus americanus) commonly ...