An unbiased estimator with prior information
Joint Authors
Luqman, Adewale F.
Ayinde, Kayode
Aladeitan, Benedicta
Bamidele, Rasak
Source
Arab Journal of Basic and Applied Sciences
Issue
Vol. 27, Issue 1 (30 Jun. 2020), pp.44-55, 12 p.
Publisher
University of Bahrain College of Science
Publication Date
2020-06-30
Country of Publication
Bahrain
No. of Pages
12
Main Subjects
Abstract EN
The ordinary least square (OLS) estimator suffers a breakdown in the presence of multicollinearity.
The estimator is still unbiased but possesses a significant variance.
In this study, we proposed an unbiased modified ridge-type estimator as an alternative to the OLS estimator and the biased estimators for handling multicollinearity in linear regression models.
The properties of this new estimator were derived.
The estimator is also unbiased with minimum variance.
A real-life application to the higher heating value of poultry waste from proximate analysis and simulation study generally supported the findings
American Psychological Association (APA)
Luqman, Adewale F.& Ayinde, Kayode& Aladeitan, Benedicta& Bamidele, Rasak. 2020. An unbiased estimator with prior information. Arab Journal of Basic and Applied Sciences،Vol. 27, no. 1, pp.44-55.
https://search.emarefa.net/detail/BIM-957371
Modern Language Association (MLA)
Luqman, Adewale F.…[et al.]. An unbiased estimator with prior information. Arab Journal of Basic and Applied Sciences Vol. 27, no. 1 (2020), pp.44-55.
https://search.emarefa.net/detail/BIM-957371
American Medical Association (AMA)
Luqman, Adewale F.& Ayinde, Kayode& Aladeitan, Benedicta& Bamidele, Rasak. An unbiased estimator with prior information. Arab Journal of Basic and Applied Sciences. 2020. Vol. 27, no. 1, pp.44-55.
https://search.emarefa.net/detail/BIM-957371
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 55
Record ID
BIM-957371
