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Modern Stochastics: Theory and Applications


Jackknife covariance matrix estimation for observations from mixture
Volume 6, Issue 4 (2019), pp. 495–513
Pub. online: 7 November 2019      Type: Research Article      Open accessOpen Access
Received
20 May 2019
Revised
7 September 2019
Accepted
14 October 2019
Published
7 November 2019

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.

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© 2019 The Author(s). Published by VTeX
Open access article under the CC BY license.

Keywords
Finite mixture model orthogonal regression mixture with varying concentrations nonparametric estimation asymptotic covariance matrix estimation confidence ellipsoid jackknife errors-in-variables model

MSC2010
62J05 62G20

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