D. O. Loftsgaarden, C. P. Quesenberry, A Nonparametric Estimate of a Multivariate Density Function, The Annals of Mathematical Statistics, Vol. 36, No. 3 (Jun., 1965 ...

We consider the problem of learning smooth multivariate probability density functions. We invoke the canonical decomposition of multivariate functions and we show that if a joint probability density ...

Learn how to use kernel density estimation, a technique that approximates the probability density function of a random variable in machine learning, and how to choose the best kernel function and ...

A non-Bayesian derivation of the predictive estimate of a multivariate normal density function is given. The estimate is obtained as best invariant estimate in terms of a goodness-of-fit criterion ...

Probability density function is a statistical expression defining the likelihood of a series of outcomes for a continuous variable, such as a stock or ETF return.

Presents two robust solutions to the control of the output probability density function for general multi-input and multi-output stochastic systems. The control inputs of the system appear as a set of ...