Linear regression by observations from mixture with varying concentrations

Liubashenko, Daryna; Maiboroda, Rostyslav

doi:10.15559/15-VMSTA41

Modern Stochastics: Theory and Applications

Linear regression by observations from mixture with varying concentrations

Volume 2, Issue 4 (2015), pp. 343–353

Daryna Liubashenko Rostyslav Maiboroda

https://doi.org/10.15559/15-VMSTA41

Pub. online: 4 December 2015 Type: Research Article

Open Access

Received
20 October 2015

Revised
22 November 2015

Accepted
26 November 2015

Published
4 December 2015

Abstract

We consider a finite mixture model with varying mixing probabilities. Linear regression models are assumed for observed variables with coefficients depending on the mixture component the observed subject belongs to. A modification of the least-squares estimator is proposed for estimation of the regression coefficients. Consistency and asymptotic normality of the estimates is demonstrated.

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Keywords

Finite mixture model linear regression mixture with varying concentrations nonparametric estimation asymptotic normality consistency

MSC2010

62J05 62G20

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