Statistical inference on restricted partial linear regression models with partial distortion measurement errors

We consider the estimation and hypothesis testing problems for the partial linear regression models when some variables are distorted with errors by some unknown functions of commonly observable confounding variable. The proposed estimation procedure is designed to accommodate undistorted as well as distorted variables. To test a hypothesis on the parametric components, a restricted least squares estimator is proposed under the null hypothesis. Asymptotic properties for the estimators are established. A test statistic based on the difference between the residual sums of squares under the null... Mehr ...

Verfasser: Zhang, Jun
Dokumenttyp: Artikel
Reihe/Periodikum: Statistica Neerlandica
Verlag/Hrsg.: Oxford, Blackwell
Sprache: Englisch
ISSN: 0039-0402
Weitere Identifikatoren: doi: 10.1111/stan.12089
Permalink: https://search.fid-benelux.de/Record/olc-benelux-1984451278
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Datenquelle: Online Contents Benelux; Originalkatalog
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Link(s) : http://dx.doi.org/10.1111/stan.12089
http://dx.doi.org/10.1111/stan.12089
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