Muhammad Qasim
Universitetsadjunkt
On Some Weighted Mixed Ridge Regression Estimators : Theory, Simulation and Application
Författare
Redaktör
- Aliaa Burqan
- Rania Saadeh
- Ahmad Qazza
- Osama Yusuf Ababneh
- Juan C. Cortés
- Kai Diethelm
- Dia Zeidan
Summary, in English
Comparisons among some new types of weighted mixed regression estimators for the linear regression model under the stochastic linear restrictions have been made in this paper. The mean squared error criterion is used to examine the superiority of different weighted mixed regression estimators. A Monte Carlo simulation study and real-life application are carried out to compare the performance of these estimators for different cases. Finally, we suggest the best weighted mixed regression estimator with collinear regressors.
Publiceringsår
2024
Språk
Engelska
Sidor
69-88
Publikation/Tidskrift/Serie
Springer Proceedings in Mathematics and Statistics
Dokumenttyp
Konferenspaper i proceeding
Förlag
Springer Gabler
Ämne
- Probability Theory and Statistics
Nyckelord
- Low-fat milk application
- Multicollinearity
- Stochastic restrictions
- Weighted mixed almost unbiased ridge estimator
- Weighted mixed estimator
- Weighted mixed ridge estimator
Conference name
8th International Arab Conference on Mathematics and Computations, IACMC 2023
Conference date
2023-05-10 - 2023-05-12
Conference place
Zarqa, Jordan
Aktiv
Published
Report number
466
ISBN/ISSN/Övrigt
- ISBN: 9789819748754
- ISSN: 2194-1017
- ISSN: 2194-1009