On some beta ridge regression estimators: method, simulation and application
| العنوان: | On some beta ridge regression estimators: method, simulation and application |
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| المؤلفون: | Qasim, Muhammad, Månsson, Kristofer, 1983, Golam Kibria, B. M. Golam |
| المصدر: | Journal of Statistical Computation and Simulation. 91(9):1699-1712 |
| مصطلحات موضوعية: | Beta regression model, mean Squared error, median Squared error, multicollinearity, simulation study |
| الوصف: | The classic statistical method for modelling the rates and proportions is the beta regression model (BRM). The standard maximum likelihood estimator (MLE) is used to estimate the coefficients of the BRM. However, this MLE is very sensitive when the regressors are linearly correlated. Therefore, this study introduces a new beta ridge regression (BRR) estimator as a remedy to the problem of instability of the MLE. We study the mean squared error properties of the BRR estimator analytically and then based on the derived MSE, we suggest some new estimators of the shrinkage parameter. We also suggest a median squared error (SE) performance criterion, which can be used to achieve strong evidence in favour of the proposed method for the Monte Carlo simulation study. The performance of BRR and MLE is appraised through Monte Carlo simulation. Finally, an empirical application is used to show the advantages of the proposed estimator. |
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| URL الوصول: | https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-51662 https://doi.org/10.1080/00949655.2020.1867549 |
| قاعدة البيانات: | SwePub |
PDF full text from Publisher | تدمد: | 00949655 15635163 |
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| DOI: | 10.1080/00949655.2020.1867549 |