Nature

Shrinkage Estimation and Balanced Loss Functions in Multivariate Normal Distribution

Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...
JSTOR Daily

Inference in the Growth Curve Model under Multivariate Skew Normal Distribution

Sankhyā: The Indian Journal of Statistics, Series B (2008-), Vol. 82, No. 1 (May 2020), pp. 34-69 (36 pages) Existing methods for estimating the parameters of the Growth Curve Model (GCM) rely on the ...
JSTOR Daily

A Two-Stage Test for the Mean of a Multivariate Normal Distribution with Known Covariance Matrix

Sankhyā: The Indian Journal of Statistics, Series B (1960-2002), Vol. 51, No. 3 (Dec., 1989), pp. 425-428 (4 pages) A two-stage analogue of the chi-square test for the mean of a multivariate normal ...
Simon Fraser University

Measures of Multivariate Kurtosis

In many applications, the manifest variables are not even approximately multivariate normal. If this happens to be the case with your data set, the default generalized least-squares and maximum ...
IEEE

Robust Kalman Filtering Based on Multivariate Geometric Skew Normal Distribution

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 ...
Risk

Modeling electricity forward prices using the multivariate normal inverse Gaussian distribution

This paper presents a discrete random-field model for forward prices driven by the multivariate normal inverse Gaussian distribution. The model captures the idiosyncratic risk and adequately addresses ...