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Emami H. Ridge stochastic restricted estimators in semiparametric linear measurement error models. JIRSS. 2017; 18 (1)
URL: http://jirss.irstat.ir/article-1-442-en.html
Abstract:   (92 Views)

In this article we consider the stochastic restricted ridge estimation in semipara-
metric linear models when the covariates are measured with additive errors. The
development of penalized corrected likelihood method in such model is the ba-
sis for derivation of ridge estimates. The asymptotic normality of the resulting
estimates are established. Also, necessary and sufficient conditions, for the su-
periority of the proposed estimator over its counterpart, for selecting the ridge
parameter k are obtained. A Monte Carlo simulation study is also performed
to illustrate the finite sample performance of the proposed procedures. Finally
theoretical results are applied to Egyptian pottery Industry data set.

     
Type of Study: Original Paper | Subject: 62Jxx: Linear inference, regression
Received: 2017/07/20 | Accepted: 2018/02/5

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