Genome-Wide Association Studies (GWAS) have transformed human genetics by identifying thousands of loci associated with complex traits and diseases. Yet, individual GWAS are often underpowered, and ...

Multivariate normality testing plays a critical role in modern statistical analysis by evaluating whether a multivariate dataset conforms to the assumptions of a normal distribution. Such assessments ...

Abstract: This paper introduces a novel robust Kalman filter, referred to as the robust Kalman filter based on multivariate geometric skew normal (MGSN) distribution (RKF-MGSN). The RKF -MGSN ...

Add a description, image, and links to the multivariate-normal-distribution topic page so that developers can more easily learn about it.

ABSTRACT: Using the results of a unique telephone survey the frequency of consumer flights from airports in a multi-airport region are modeled using a multivariate Poisson framework, the parameters of ...

Abstract: Nowadays, computer games have gained immense popularity, captivating gamers who can easily spend hours engrossed in their laptops. However, not every game has the ability to keep players ...

Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets ...