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Journals / Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi / 2020 / Cilt: 36 - Sayı: 3

Mean Square Error Performance of the Modified Jackknifed Ridge Predictors in the Linear Mixed Models

Özge KURAN
Pages
400–407
Publication Date
2020-12-31
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, a real data analysis is given to observe the behavior of the modified jackknifed ridge predictors.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The goal of this study is to introduce the modified jackknifed ridge prediction method in the linear mixed models.
📊
Key Findings & Data:Then, the matrix mean square error (MMSE) comparisons are done.
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Conclusion & Impact:Finally, a real data analysis is given to observe the behavior of the modified jackknifed ridge predictors.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Jackknifed ridge predictors · Linear mixed models · Modified jackknified ridge predictors

Özet

The goal of this study is to introduce the modified jackknifed ridge prediction method in the linear mixed models. Then, the matrix mean square error (MMSE) comparisons are done. Finally, a real data analysis is given to observe the behavior of the modified jackknifed ridge predictors.

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Cite This Article

KURAN, Ö. (2020). Mean Square Error Performance of the Modified Jackknifed Ridge Predictors in the Linear Mixed Models. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, Cilt: 36 - Sayı: 3, 400–407. https://ajindex.com/articles/252990

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