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On Some Weighted Mixed Ridge Regression Estimators : Theory, Simulation and Application

Alheety, Mustafa I. ; Qasim, Muhammad LU ; Månsson, Kristofer and Kibria, B. M.Golam (2024) 8th International Arab Conference on Mathematics and Computations, IACMC 2023 In Springer Proceedings in Mathematics and Statistics 466. p.69-88
Abstract

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.

Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Low-fat milk application, Multicollinearity, Stochastic restrictions, Weighted mixed almost unbiased ridge estimator, Weighted mixed estimator, Weighted mixed ridge estimator
host publication
Mathematical Analysis and Numerical Methods - IACMC 2023
series title
Springer Proceedings in Mathematics and Statistics
editor
Burqan, Aliaa ; Saadeh, Rania ; Qazza, Ahmad ; Ababneh, Osama Yusuf ; Cortés, Juan C. ; Diethelm, Kai and Zeidan, Dia
volume
466
pages
20 pages
publisher
Springer Gabler
conference name
8th International Arab Conference on Mathematics and Computations, IACMC 2023
conference location
Zarqa, Jordan
conference dates
2023-05-10 - 2023-05-12
external identifiers
  • scopus:85206875980
ISSN
2194-1017
2194-1009
ISBN
9789819748754
DOI
10.1007/978-981-97-4876-1_6
language
English
LU publication?
no
additional info
Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
id
b6df1a40-bfde-4bc4-92cb-d155d3f72ce4
date added to LUP
2025-01-20 12:40:49
date last changed
2025-07-08 02:13:15
@inproceedings{b6df1a40-bfde-4bc4-92cb-d155d3f72ce4,
  abstract     = {{<p>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.</p>}},
  author       = {{Alheety, Mustafa I. and Qasim, Muhammad and Månsson, Kristofer and Kibria, B. M.Golam}},
  booktitle    = {{Mathematical Analysis and Numerical Methods - IACMC 2023}},
  editor       = {{Burqan, Aliaa and Saadeh, Rania and Qazza, Ahmad and Ababneh, Osama Yusuf and Cortés, Juan C. and Diethelm, Kai and Zeidan, Dia}},
  isbn         = {{9789819748754}},
  issn         = {{2194-1017}},
  keywords     = {{Low-fat milk application; Multicollinearity; Stochastic restrictions; Weighted mixed almost unbiased ridge estimator; Weighted mixed estimator; Weighted mixed ridge estimator}},
  language     = {{eng}},
  month        = {{10}},
  pages        = {{69--88}},
  publisher    = {{Springer Gabler}},
  series       = {{Springer Proceedings in Mathematics and Statistics}},
  title        = {{On Some Weighted Mixed Ridge Regression Estimators : Theory, Simulation and Application}},
  url          = {{http://dx.doi.org/10.1007/978-981-97-4876-1_6}},
  doi          = {{10.1007/978-981-97-4876-1_6}},
  volume       = {{466}},
  year         = {{2024}},
}