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On the fourth-order hybrid beta polynomial kernels in kernel density estimation.

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Titel: On the fourth-order hybrid beta polynomial kernels in kernel density estimation.
Autoren: Afere, Benson Ade Eniola
Quelle: Journal of Nigerian Society of Physical Sciences; Feb2024, Vol. 6 Issue 1, p1-15, 15p
Schlagwörter: POLYNOMIALS, QUANTITATIVE research, KERNEL (Mathematics), DATA analysis, EVALUATION
Abstract: This paper introduces a novel family of fourth-order hybrid beta polynomial kernels tailored for statistical analysis. The efficacy of these kernels is evaluated using two principal performance metrics: asymptotic mean integrated squared error (AMISE) and kernel efficiency. Comprehensive assessments were conducted using both simulated and real-world datasets, enabling a thorough comparison with conventional fourth-order polynomial kernels. The evaluation process entailed computing AMISE and efficiency metrics for both the hybrid and classical kernels. Consistently, the results illustrated the superior performance of the hybrid kernels over their classical counterparts across diverse datasets, underscoring the robustness and effectiveness of the hybrid approach. By leveraging these performance metrics and conducting evaluations on simulated and realworld data, this study furnishes compelling evidence supporting the superiority of the proposed hybrid beta polynomial kernels. The heightened performance, evidenced by lower AMISE values and elevated efficiency scores, strongly advocates for the adoption of the proposed kernels in statistical analysis tasks, presenting a marked improvement over traditional kernels. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Nigerian Society of Physical Sciences is the property of Nigerian Society of Physical Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Datenbank: Biomedical Index
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: On the fourth-order hybrid beta polynomial kernels in kernel density estimation.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Afere%2C+Benson+Ade+Eniola%22">Afere, Benson Ade Eniola</searchLink>
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  Data: Journal of Nigerian Society of Physical Sciences; Feb2024, Vol. 6 Issue 1, p1-15, 15p
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  Data: <searchLink fieldCode="DE" term="%22POLYNOMIALS%22">POLYNOMIALS</searchLink><br /><searchLink fieldCode="DE" term="%22QUANTITATIVE+research%22">QUANTITATIVE research</searchLink><br /><searchLink fieldCode="DE" term="%22KERNEL+%28Mathematics%29%22">KERNEL (Mathematics)</searchLink><br /><searchLink fieldCode="DE" term="%22DATA+analysis%22">DATA analysis</searchLink><br /><searchLink fieldCode="DE" term="%22EVALUATION%22">EVALUATION</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper introduces a novel family of fourth-order hybrid beta polynomial kernels tailored for statistical analysis. The efficacy of these kernels is evaluated using two principal performance metrics: asymptotic mean integrated squared error (AMISE) and kernel efficiency. Comprehensive assessments were conducted using both simulated and real-world datasets, enabling a thorough comparison with conventional fourth-order polynomial kernels. The evaluation process entailed computing AMISE and efficiency metrics for both the hybrid and classical kernels. Consistently, the results illustrated the superior performance of the hybrid kernels over their classical counterparts across diverse datasets, underscoring the robustness and effectiveness of the hybrid approach. By leveraging these performance metrics and conducting evaluations on simulated and realworld data, this study furnishes compelling evidence supporting the superiority of the proposed hybrid beta polynomial kernels. The heightened performance, evidenced by lower AMISE values and elevated efficiency scores, strongly advocates for the adoption of the proposed kernels in statistical analysis tasks, presenting a marked improvement over traditional kernels. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Nigerian Society of Physical Sciences is the property of Nigerian Society of Physical Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.46481/jnsps.2024.1631
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 1
    Subjects:
      – SubjectFull: POLYNOMIALS
        Type: general
      – SubjectFull: QUANTITATIVE research
        Type: general
      – SubjectFull: KERNEL (Mathematics)
        Type: general
      – SubjectFull: DATA analysis
        Type: general
      – SubjectFull: EVALUATION
        Type: general
    Titles:
      – TitleFull: On the fourth-order hybrid beta polynomial kernels in kernel density estimation.
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            NameFull: Afere, Benson Ade Eniola
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            – D: 01
              M: 02
              Text: Feb2024
              Type: published
              Y: 2024
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