Ridge Stochastic Restricted Estimators in Semiparametric Lin-ear Measurement Error Models

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EMAMI HADI

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Journal Paper

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Journal: Journal of the Iranian Statistical Society Year:2018 | Volume:17 | Issue:2 Page(s): 181-203

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Title

Ridge Stochastic Restricted Estimators in Semiparametric Lin-ear Measurement Error Models

Author(s)

EMAMI HADI | Issue Writer Certificate

Keywords

Cross validation

Measurement error

Multicollinearity

Semiparametric linear regression

Shrinkage estimator

Abstract

In this article we consider the stochastic restricted ridge estimation in semi-parametric linear models when the covariates are measured with additive errors. The development of penalized corrected likelihood method in such model is the basis for derivation of ridge estimates. The asymptotic normality of the resulting estimates are established. Also, necessary and sufficient conditions, for the superiority of the pro-posed 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 perfor-mance of the proposed procedures. Finally theoretical results are applied to Egyptian pottery Industry data set.

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APA: Copy

EMAMI, HADI. (2018). Ridge Stochastic Restricted Estimators in Semiparametric Lin-ear Measurement Error Models. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), 17(2), 181-203. SID. https://sid.ir/paper/749338/en

Vancouver: Copy

EMAMI HADI. Ridge Stochastic Restricted Estimators in Semiparametric Lin-ear Measurement Error Models. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS)[Internet]. 2018;17(2):181-203. Available from: https://sid.ir/paper/749338/en

IEEE: Copy

HADI EMAMI, “Ridge Stochastic Restricted Estimators in Semiparametric Lin-ear Measurement Error Models,” JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), vol. 17, no. 2, pp. 181–203, 2018, [Online]. Available: https://sid.ir/paper/749338/en

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