DeepAI AI Chat

On the variability of the sample covariance matrix under complex elliptical distributions

08/18/2021

∙

by Elias Raninen, et al.

∙

∙

We derive the variance-covariance matrix of the sample covariance matrix (SCM) as well as its theoretical mean squared error (MSE) when sampling from complex elliptical distributions with finite fourth-order moments. We also derive the form of the variance-covariance matrix for any affine equivariant matrix-valued statistics. Finally, illustrative examples of the formulas are presented.

Elias Raninen
4 publications
Esa Ollila
21 publications
David E. Tyler
5 publications

page 1

page 2

page 3

page 4

∙ 09/03/2021

Regularized tapered sample covariance matrix

Covariance matrix tapers have a long history in signal processing and re...

0 Esa Ollila, et al. ∙

∙ 04/12/2022

Portfolio Optimization Using a Consistent Vector-Based MSE Estimation Approach

This paper is concerned with optimizing the global minimum-variance port...

0 Maaz Mahadi, et al. ∙

∙ 08/13/2020

Linear pooling of sample covariance matrices

We consider covariance matrix estimation in a setting, where there are m...

0 Elias Raninen, et al. ∙

∙ 10/02/2018

On characterizations of the covariance matrix

The covariance matrix is well-known for its following properties: affine...

0 Joni Virta, et al. ∙

∙ 10/15/2018

Population Symbolic Covariance Matrices for Interval Data

Symbolic Data Analysis (SDA) is a relatively new field of statistics tha...

0 M. Rosário Oliveira, et al. ∙

∙ 11/27/2022

Generalizing Gaussian Smoothing for Random Search

Gaussian smoothing (GS) is a derivative-free optimization (DFO) algorith...

0 Katelyn Gao, et al. ∙

∙ 01/29/2019

Statistical inference of probabilistic origin-destination demand using day-to-day traffic data

Recent transportation network studies on uncertainty and reliability cal...

0 Wei Ma, et al. ∙