A mixture density network (MDN) Layer for Keras using pure Keras 3 operations. This makes it a bit more simple to experiment with neural networks that predict multiple real-valued variables that can ...

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 ...

Abstract: In this letter, we discuss the multivariate Laplace probability model in the context of a normal variance mixture model. We briefly review the derivation of the probability density function ...

This repository contains the source files for the R package JMbayes. This package fits joint models for longitudinal and time-to-event data under a Bayesian approach using MCMC. These models are ...

Divisive normalization is a ubiquitous computation commonly thought to be an implementation of the efficient coding principle. Despite empirical evidence that it reduces statistical redundancy present ...

In this study, to power comparison test, different univariate normality testing procedures are compared by using new algorithm. Different univariate and multivariate test are also analyzed here. And ...

Department of Chemistry, Texas A&M University, College Station, Texas 77843-3255, United States College of Chemistry, Tianjin Normal University, Tianjin, 300387, China Key Laboratory of Advanced ...

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 ...