Linear regression by observations from mixture with varying concentrations

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.

Keywords

• Finite mixture model
• Linear regression
• mixture with varying concentrations
• nonparametric estimation
• Asymptotic normality
• consistency