Detection of outliers and influential observations in linear mixed measurement error models with Liu estimation
سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 42
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شناسه ملی سند علمی:
JR_JSMTA-4-2_001
تاریخ نمایه سازی: 2 تیر 1403
چکیده مقاله:
In this paper, the case deletion approach and mean shift outlier model are developed to identify influential and outlier observations using the Liu corrected likelihood estimator in linear mixed measurement error models when multicollinearity is present. We derive a corrected score test statistic for outlier detection based on mean shift outlier models. Furthermore, according to the Liu corrected likelihood estimator, several Cook’s distance is constructed for influence diagnostics. A parametric bootstrap procedure is used to obtain empirical distribution of the test statistic and a simulation study is conducted to demonstrate the performance of the diagnostic criteria. Finally, a real example is provided to illustrate the performance of the test statistics.
کلیدواژه ها:
نویسندگان
Shadi Borhani
Department of Statistics, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran
Fatemeh Ghapani
Department of Mathematics and Statistics, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran
Razieh Jafaraghaee
Department of Mathematics and Statistics, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran