Halva—‘grapHical Analysis with Latent VAriables’—is a Python package dedicated to statistical analysis of multivariate ordinal data, designed specifically to handle missing values and latent variables ...
ABSTRACT: In a previous article, an R script was developed and divided into three parts to implement the multivariate normality (MVN) Q-test based on both the chi-square approximation and the ...
Introduction: Accurately predicting the remaining mechanical equipment is of great significance for ensuring the safe operation of the equipment and improving economic efficiency. Methods: To ...
Abstract: Missing values means the absence of data items for an observation that can result in the loss of certain information. During surveys, there are often missing values or missing data because ...
Abstract: In statistics, the concept of a concomitant, also called the induced order statistic, arises when one sorts the members of a random sample according to corresponding values of another random ...
excerpt: "Given a covariance matrix and a mean vector, how do we generate random vectors from the corresponding Gaussian model?" You may have used `mvnrnd` in Matlab or `multivariate_normal` in NumPy.
Multivariate analysis of variance (MANOVA) is a widely used technique for simultaneously comparing means for multiple dependent variables across two or more groups. MANOVA rests on several assumptions ...
We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and ...
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