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Almost unbiased rid...
Almost unbiased ridge estimator in the gamma regression model
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- Amin, Muhammad (författare)
- Department of Statistics, University of Sargodha, Sargodha, Pakistan
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- Qasim, Muhammad (författare)
- Jönköping University,IHH, Statistik
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- Yasin, Ahad (författare)
- Department of Statistics, University of Sargodha, Sargodha, Pakistan
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- Amanullah, Muhammad (författare)
- Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan
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(creator_code:org_t)
- 2020-02-10
- 2022
- Engelska.
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Ingår i: Communications in statistics. Simulation and computation. - : Taylor & Francis. - 0361-0918 .- 1532-4141. ; 51:7, s. 3830-3850
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- This article introduces the almost unbiased gamma ridge regression estimator (AUGRRE) estimator based on the gamma ridge regression estimator (GRRE). Furthermore, some shrinkage parameters are proposed for the AUGRRE. The performance of the AUGRRE by using different shrinkage parameters is compared with the existing GRRE and maximum likelihood estimator. A Monte Carlo simulation is carried out to assess the performance of the estimators where the bias and mean squared error performance criteria are used. We also used a real-life dataset to demonstrate the benefit of the proposed estimators. The simulation and real-life example results show the superiority of AUGRRE over the GRRE and the maximum likelihood estimator for the gamma regression model with collinear explanatory variables.
Ämnesord
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Gamma regression
- Multicollinearity
- Almost unbiased gamma ridge regression
- Monte Carlo simulation
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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