Stochastic Restricted Biased Estimators in Misspecified Regression Model with Incomplete Prior Information

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dc.contributor.author Kayanan, M.
dc.contributor.author Wijekoon, P.
dc.date.accessioned 2022-05-11T05:13:47Z
dc.date.available 2022-05-11T05:13:47Z
dc.identifier.uri http://drr.vau.ac.lk/handle/123456789/87
dc.description.abstract The analysis of misspecification was extended to the recently introduced stochastic restricted biased estimators when multi collinearity exists among the explanatory variables. The Stochastic Restricted Ridge Estimator (SRRE), Stochastic Restricted Almost Unbiased Ridge Estimator (SRAURE), Stochastic Restricted Liu Estimator (SRLE), Stochastic Restricted Almost Unbiased Liu Estimator (SRAULE), Stochastic Restricted Principal Component Regression Estimator (SRPCRE), Stochastic Restricted (SRrk) class estimator, and Stochastic Restricted (SRrd) class estimator were examined in the misspecified regression model due to missing relevant explanatory variables when incomplete prior information of the regression coefficients is available. Further, the superiority conditions between estimators and their respective predictors were obtained in the mean square error matrix (MSEM) sense. Finally, a numerical example and a Monte Carlo simulation study were used to illustrate the theoretical findings en_US
dc.language.iso en en_US
dc.publisher Hindawi en_US
dc.subject Misspecified regression model en_US
dc.subject Generalized stochastic restricted estimator en_US
dc.subject Mean square error matrix en_US
dc.subject Monte Carlo simulation en_US
dc.title Stochastic Restricted Biased Estimators in Misspecified Regression Model with Incomplete Prior Information en_US
dc.type Article en_US
dc.identifier.doi https://doi.org/10.1155/2018/1452181 en_US
dc.identifier.journal Journal of Probability and Statistics en_US


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