On the repeated inversion of a covariance matrix

08/25/2017
by   M. de Jong, et al.
0

In many cases, the values of some model parameters are determined by maximising the likelihood of a set of data points given the parameter values. The presence of outliers in the data and correlations between data points complicate this procedure. An efficient procedure for the elimination of outliers is presented which takes the correlations between data points into account.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/12/2020

Covariance matrix filtering with bootstrapped hierarchies

Statistical inference of the dependence between objects often relies on ...
research
01/31/2017

Prototypal Analysis and Prototypal Regression

Prototypal analysis is introduced to overcome two shortcomings of archet...
research
07/08/2020

Robust Concordance Rate for A Four-Quadrant Plot

Before new clinical measurement methods are implemented in clinical prac...
research
12/11/2021

Test Set Sizing Via Random Matrix Theory

This paper uses techniques from Random Matrix Theory to find the ideal t...
research
07/05/2022

Post-hoc regularisation of unfolded cross-section measurements

Neutrino cross-section measurements are often presented as unfolded binn...
research
05/03/2018

A generalized spatial sign covariance matrix

The well-known spatial sign covariance matrix (SSCM) carries out a radia...
research
09/12/2017

Community Recovery in Hypergraphs

Community recovery is a central problem that arises in a wide variety of...

Please sign up or login with your details

Forgot password? Click here to reset