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Influence Diagnostics in Two-Parameter Ridge Regression

並列摘要


Identifying influential observations is an important part of the model building process in linear regression. There are numerous diagnostic measures based on different approaches in linear regression analysis. However, the problem of multicollinearity and influential observations may occur simultaneously. Therefore, we propose new diagnostic measures based on the two parameter ridge estimator defined by Lipovetsky and Conklin (2005) alternative to the usual ridge regression and ordinary linear regression. We define two parameter ridge-type generalizations of DFFITS and Cook’s distance. Moreover, we obtain approximate case deletion formulas and provide approximate versions of new measures. Finally, we illustrate the benefits of proposed measures in real data examples.

被引用紀錄


詹芳彬(2012)。與外界環境緊密結合之風能捕捉器整合設計〔碩士論文,國立屏東科技大學〕。華藝線上圖書館。https://doi.org/10.6346/NPUST.2012.00208

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