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Modified Liu estimator to address the multicollinearity problem in regression models: A new biased estimation class. SCIENTIFIC AFRICAN 2022. [DOI: 10.1016/j.sciaf.2022.e01372] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
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Dawoud I, Lukman AF, Haadi AR. A new biased regression estimator: Theory, simulation and application. SCIENTIFIC AFRICAN 2022. [DOI: 10.1016/j.sciaf.2022.e01100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Affiliation(s)
- Y. Murat Bulut
- Department of Statistics, Eskişehir Osmangazi University, Eskisehir, Turkey
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Dawoud I. A new improved estimator for reducing the multicollinearity effects. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.1939374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Issam Dawoud
- Mathematics Department, Al-Aqsa University, Gaza, Palestine
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A New Biased Estimator to Combat the Multicollinearity of the Gaussian Linear Regression Model. STATS 2020. [DOI: 10.3390/stats3040033] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
In a multiple linear regression model, the ordinary least squares estimator is inefficient when the multicollinearity problem exists. Many authors have proposed different estimators to overcome the multicollinearity problem for linear regression models. This paper introduces a new regression estimator, called the Dawoud–Kibria estimator, as an alternative to the ordinary least squares estimator. Theory and simulation results show that this estimator performs better than other regression estimators under some conditions, according to the mean squares error criterion. The real-life datasets are used to illustrate the findings of the paper.
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6
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Affiliation(s)
- Esra Ertan
- Department of Mathematics, Science Faculty, University of Istanbul, Istanbul, Turkey
| | - Kadri Ulaş Akay
- Department of Mathematics, Science Faculty, University of Istanbul, Istanbul, Turkey
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Naveed K, Amin M, Afzal S, Qasim M. New shrinkage parameters for the inverse Gaussian Liu regression. COMMUN STAT-THEOR M 2020. [DOI: 10.1080/03610926.2020.1791339] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Khalid Naveed
- Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan
| | - Muhammad Amin
- Department of Statistics, University of Sargodha, Sargodha, Pakistan
| | - Saima Afzal
- Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan
| | - Muhammad Qasim
- Department of Economics, Finance and Statistics, Jönköping International Business School, Jönköping University, Sweden
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8
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Qasim M, Amin M, Amanullah M. On the performance of some new Liu parameters for the gamma regression model. J STAT COMPUT SIM 2018. [DOI: 10.1080/00949655.2018.1498502] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- Muhammad Qasim
- Department of Statistics and Computer Science, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | - Muhammad Amin
- Department of Statistics, University of Sargodha, Sargodha, Pakistan
| | - Muhammad Amanullah
- Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan
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