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JSRI 2015, 12(1): 39-56 Back to browse issues page
Influence Measures in Ridge Linear Measurement Error Models
Hadi Emami
, h.emami@znu.ac.ir
Abstract:   (4560 Views)

Usually the existence of influential observations is complicated by the presence of collinearity in linear measurement error models. However no method of influence measure available for the possible effect's that collinearity can have on the influence of an observation in such models. In this paper, a new type of ridge estimator based corrected likelihood function (REC) for linear measurement error models is defined. We show when this type of ridge estimator is used to mitigate the effects of collinearity the influence of some observations can be drastically modified. We propose a case deletion formula to detect influential points in REC. As an illustrative example two real data set are analysed. 

Keywords: Corrected likelihood, diagnostics, leverage, measurement error models, shrinkage estimators.
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Type of Study: Research | Subject: General
Received: 2015/11/14 | Accepted: 2015/11/14 | Published: 2015/11/14
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Emami H. Influence Measures in Ridge Linear Measurement Error Models. JSRI 2015; 12 (1) :39-56
URL: http://jsri.srtc.ac.ir/article-1-23-en.html

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Volume 12, Issue 1 (9-2015) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران Journal of Statistical Research of Iran JSRI
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