Estimation and testing for partially functional linear errors-in-variables models

Hanbing Zhu, Riquan Zhang, Zhou Yu, Heng Lian and Yanghui Liu

Journal of Multivariate Analysis, 2019, vol. 170, issue C, 296-314

Abstract: This paper considers estimation and testing problems for partial functional linear models when the covariates in the non-functional linear component are measured with additive error. A corrected profile, least-squares based, estimation procedure is developed for the parametric component. Asymptotic properties of the proposed estimators are established under some regularity conditions. To test a hypothesis on the parametric component, a statistic based on the difference between the corrected residual sums of squares under the null and alternative hypotheses is proposed; its limiting null distribution is shown to be a weighted sum of independent standard χ12 variables. Simulation studies are conducted to demonstrate the performance of the proposed procedure and a real example is analyzed for illustration.

Keywords: Corrected profile least-squares; Errors-in-variables; Functional data; Hypothesis test; Partially linear models (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:170:y:2019:i:c:p:296-314

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DOI: 10.1016/j.jmva.2018.11.005

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