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  <doi_batch_id>aspg-39-3028-1792222466</doi_batch_id>
  <timestamp>20261017073426</timestamp>
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   <depositor_name>American Scientific Publishing Group</depositor_name>
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  <journal>
   <journal_metadata language="en">
    <full_title>Neutrosophic and Information Fusion</full_title>
    <abbrev_title>NIF</abbrev_title>
    <issn media_type="electronic">2836-7863</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <journal_volume>
     <volume>3</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>On the Bayesian Estimation of Parameters of SQDM</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Murtada Ali</given_name>
      <surname>Maqdisi</surname>
      <affiliations>
       <institution>
        <institution_name>College of Pharmacy, AL-Farahidi University, Baghdad, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>This work is concerned with the problem of estimating parameters of spatial quadratic models by the Bayesian technique (SQDM). This technique involves prior information on the first and second moments of the parameters, where its estimation model is called the Bayesian quadratic unbiased estimator. The results of the estimation are compared with the estimates of minimum-norm quadratic unbiased estimators.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2024</year>
    </publication_date>
    <pages>
     <first_page>24</first_page>
     <last_page>28</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">3028</item_number>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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     <doi>10.54216/NIF.030105</doi>
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