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Dergiler / Hacettepe Journal of Mathematics and Statistics / 2023 / Cilt: 52 Sayı: 3

The beta Liu-type estimator: simulation and application

Ali ERKOÇ
Esra ERTAN
Zakariya Yahya ALGAMAL
Kadri Ulaş AKAY
Sayfa
828–840
Yayın Tarihi
2023-05-30
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Finally, a numerical example is given to show the benefit of the proposed estimator over existing estimators.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:The Beta Regression Model (BRM) is commonly used while analyzing data where the dependent variable is restricted to the interval $[0,1]$ for example proportion or probability.
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Temel Bulgular & Veri:The performance of the proposed new estimator is compared to the MLE and other biased estimators in terms of the Estimated Mean Squared Error (EMSE) criterion by conducting a simulation study.
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Sonuç & Katkı:Finally, a numerical example is given to show the benefit of the proposed estimator over existing estimators.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Beta regression model · Liu-type estimator · maximum likelihood estimator

Abstract

The Beta Regression Model (BRM) is commonly used while analyzing data where the dependent variable is restricted to the interval $[0,1]$ for example proportion or probability. The Maximum Likelihood Estimator (MLE) is used to estimate the regression coefficients of BRMs. But in the presence of multicollinearity, MLE is very sensitive to high correlation among the explanatory variables. For this reason, we introduce a new biased estimator called the Beta Liu-Type Estimator (BLTE) to overcome the multicollinearity problem in the case that dependent variable follows a Beta distribution. The proposed estimator is a general estimator which includes other biased estimators, such as the Ridge Estimator, Liu Estimator, and the estimators with two biasing parameters as special cases in BRM. The performance of the proposed new estimator is compared to the MLE and other biased estimators in terms of the Estimated Mean Squared Error (EMSE) criterion by conducting a simulation study. Finally, a numerical example is given to show the benefit of the proposed estimator over existing estimators.

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Bu Makaleye Atıf Yap

ERKOÇ, A., ERTAN, E., ALGAMAL, Z. Y., AKAY, K. U. (2023). The beta Liu-type estimator: simulation and application. Hacettepe Journal of Mathematics and Statistics, Cilt: 52 Sayı: 3, 828–840. https://ajindex.com/articles/920212

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Kaynakça (17)

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