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Bootstrap-quantile ridge estimator for linear regression with applications.

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  • المؤلفون: Dar IS;Dar IS; Chand S; Chand S
  • المصدر:
    PloS one [PLoS One] 2024 Apr 29; Vol. 19 (4), pp. e0302221. Date of Electronic Publication: 2024 Apr 29 (Print Publication: 2024).
  • نوع النشر :
    Journal Article; Research Support, Non-U.S. Gov't
  • اللغة:
    English
  • معلومة اضافية
    • المصدر:
      Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
    • بيانات النشر:
      Original Publication: San Francisco, CA : Public Library of Science
    • الموضوع:
      Monte Carlo Method*; Linear Models ; Computer Simulation ; Humans ; Algorithms ; Models, Statistical
    • نبذة مختصرة :
      Bootstrap is a simple, yet powerful method of estimation based on the concept of random sampling with replacement. The ridge regression using a biasing parameter has become a viable alternative to the ordinary least square regression model for the analysis of data where predictors are collinear. This paper develops a nonparametric bootstrap-quantile approach for the estimation of ridge parameter in the linear regression model. The proposed method is illustrated using some popular and widely used ridge estimators, but this idea can be extended to any ridge estimator. Monte Carlo simulations are carried out to compare the performance of the proposed estimators with their baseline counterparts. It is demonstrated empirically that MSE obtained from our suggested bootstrap-quantile approach are substantially smaller than their baseline estimators especially when collinearity is high. Application to real data sets reveals the suitability of the idea.
      Competing Interests: The authors have declared that no competing interests exist.
      (Copyright: © 2024 Dar, Chand. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
    • References:
      West J Nurs Res. 1990 Apr;12(2):175-84; discussion 184-7. (PMID: 2321373)
      Am Stat. 2015 Oct 2;69(4):371-386. (PMID: 27019512)
      Stat Appl Genet Mol Biol. 2019 Oct 7;18(5):. (PMID: 31586968)
      Scientifica (Cairo). 2020 Apr 14;2020:9758378. (PMID: 32399315)
    • الموضوع:
      Date Created: 20240429 Date Completed: 20240429 Latest Revision: 20240502
    • الموضوع:
      20240502
    • الرقم المعرف:
      PMC11057767
    • الرقم المعرف:
      10.1371/journal.pone.0302221
    • الرقم المعرف:
      38683865