Penalized proportion estimation for non parametric mixture of regressions

Qinghua Ji and Zheng Ji

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 7, 1537-1560

Abstract: In this article, we propose a penalized local log-likelihood method to locally select the number of components in non parametric finite mixture of regression models via proportion shrinkage method. Mean functions and variance functions are estimated simultaneously. We show that the number of components can be estimated consistently, and further establish asymptotic normality of functional estimates. We use a modified EM algorithm to estimate the unknown functions. Simulations are conducted to demonstrate the performance of the proposed method. We illustrate our method via an empirical analysis of the housing price index data of United States.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:49:y:2020:i:7:p:1537-1560

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DOI: 10.1080/03610926.2018.1473614

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