# This function calculates the value, in nexp experimental vectors (or scalars if dim=1) x^1,...,x^nexp stored in # the array MatRxExp(dim,nexp), of the joint probability density function of a random ...

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Density functional theory (DFT) is indubitably the most popular and among the most successful approaches for approximately solving the many-electron Schrödinger equation. The level of understanding on ...

Kernel density estimation (KDE) is a non-parametric method to estimate the probability density function of a random variable by taking the summation of kernel functions centered on each data point.

Abstract: A longstanding problem in statistics pertains to the estimation of probability density functions of continuous random variables from a finite set of their samples. In this paper, we propose ...

Abstract: This paper provides a prototype of an Electric Vehicles Load Profile Generator based on the probability density function of several parameters such as arrival time, total connection time, ...