Jackknife covariance matrix estimation for observations from mixture

TL;DR

This paper introduces a jackknife estimator for the covariance of moment estimators in mixture models, demonstrating its consistency, providing a fast computation algorithm, and applying it to regression confidence sets and sociological data analysis.

Contribution

It presents a novel jackknife covariance estimator for mixture models, with proven consistency and an efficient calculation method, extending its application to regression and sociological data.

Findings

Estimator is consistent for mixture models.

Fast algorithm for covariance estimation is developed.

Applied successfully to regression confidence sets and sociological data.

Abstract

A general jackknife estimator for the asymptotic covariance of moment estimators is considered in the case when the sample is taken from a mixture with varying concentrations of components. Consistency of the estimator is demonstrated. A fast algorithm for its calculation is described. The estimator is applied to construction of confidence sets for regression parameters in the linear regression with errors in variables. An application to sociological data analysis is considered.