Influence measures in ridge regression when the error terms follow an Ar(1) process

Computational Statistics - Tập 31 - Trang 879-898 - 2015
Tuğba Söküt Açar1, M. Revan Özkale2
1Department of Statistics, Faculty of Arts And Sciences, Çanakkale Onsekiz Mart University, Çanakkale, Turkey
2Department of Statistics, Faculty of Science and Letters, Çukurova University, Adana, Turkey

Tóm tắt

Influence concepts have an important place in linear regression models and case deletion is a useful method for assessing the influence of single case. The influence measures in the presence of multicollinearity were discussed under the linear regression models when the errors structure is uncorrelated and homoscedastic. In contrast to other article on this subject, we consider the influence measures in ridge regression with autocorrelated errors. Theoretical results are illustrated with a numerical example and a Monte Carlo simulation is conducted to see the effect autocorrelation coefficient, strength of multicollinearity and sample size on leverage points and influential observations.

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