On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression | Zendy

Chaolin Liu | Zendy; Hu Yang | Zendy; Jibo Wu | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression

Author(s) -

Chaolin Liu,

Hu Yang,

Jibo Wu

Publication year - 2013

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2013/902715

Subject(s) - estimator , mean squared error , bias of an estimator , mathematics , ridge , statistics , linear regression , best linear unbiased prediction , algorithm , computer science , minimum variance unbiased estimator , artificial intelligence , paleontology , selection (genetic algorithm) , biology

We introduce the weighted mixed almost unbiased ridge estimator (WMAURE) based on the weighted mixed estimator (WME) (Trenkler and Toutenburg 1990) and the almost unbiased ridge estimator (AURE) (Akdeniz and Erol 2003) in linear regression model. We discuss superiorities of the new estimator under the quadratic bias (QB) and the mean square error matrix (MSEM) criteria. Additionally, we give a method about how to obtain the optimal values of parameters k and w. Finally, theoretical results are illustrated by a real data example and a Monte Carlo study

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research