Frontiers

Degradation and life prediction of mechanical equipment based on multivariate stochastic process

Accurately predicting the remaining mechanical equipment is of great significance for ensuring the safe operation of the equipment and improving economic efficiency. To accurately assess the ...
GitHub

AKDE: Multivariate Adaptive Kernel Density Estimation Using Gaussian Mixture Model

AKDE provides an accurate, adaptive kernel density estimator based on the Gaussian Mixture Model for multidimensional data. This Python implementation includes automatic grid construction for ...
GitHub

Quasi-Monte-Carlo numerical computation of multivariate normal probabilities.

This function uses an algorithm given in the paper "Numerical Computation of Multivariate Normal Probabilities", in J. of Computational and Graphical Stat., 1(1992), pp. 141-149, by Alan Genz, WSU ...
Frontiers

Multivariate Correlation Measures Reveal Structure and Strength of Brain–Body Physiological Networks at Rest and During Mental Stress

In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To ...
PNAS

Reconstruction of normal forms by learning informed observation geometries from data

The extraction of models from data (in a sense, the “understanding” of the physical laws giving rise to the data) is a fundamental cognitive as well as scientific challenge. We show a ...
Scientific Research Publishing

Confidence Intervals for the Mean of Non-Normal Distribution: Transform or Not to Transform ()

1 Department of Psychology, York University, Toronto, Canada. 2 Department of Mathematics and Statistics, York University, Toronto, Canada. In many areas of applied statistics, confidence intervals ...