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  <titleInfo>
    <title>Weighted pareto distribution and related distributions</title>
  </titleInfo>
  <titleInfo type="alternative">
    <title>توزيع باريتو المرجح وتوزيعات ذات علاقة</title>
  </titleInfo>
  <name type="personal">
    <namePart>Mahmoud Abdelghaffar Mohamed Ahmed</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Mahmoud Riad Mahmoud</namePart>
    <role>
      <roleTerm type="text">Supervisor </roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Rasha Mohamed Mandouh</namePart>
    <role>
      <roleTerm type="text">Supervisor </roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">theses</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">ua</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Cairo</placeTerm>
    </place>
    <publisher>Mahmoud Abdelghaffar Mohamed Ahmed</publisher>
    <dateIssued>2019</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>88 Leaves :  charts ;  30cm </extent>
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  <abstract>The Pareto distribution, which is originally applied to describe the distribution of wealth in a society, is a power law probability distribution that is used to describe many types of observable phenomena such as social, scientific, geophysical, actuarial phenomena. The power function distribution is a special case of the Pareto distribution. It has applications in finance and economics and is used to model reliability growth of complex systems or reliability of repairable systems. Two new weighted distributions are introduced using the logarithmic weight function. These distributions are the Log-weighted Pareto distribution and the Log-weighted power function distribution. Several statistical properties of these weighted distributions are studied and derived including the cumulative distribution function, location measures such as mode, median and mean, reliability measures such as reliability function, hazard and reversed hazard functions and the mean residual life, moments, shape indices such as skewness and kurtosis coefficients and order statistics. Moreover, A parametric estimation is performed to obtain estimators for the distributions parameters using three different estimation methods; namely, the maximum likelihood method, the method of moments method and the L-moments method. Numerical simulations are carried out, for both distributions, to validate the robustness of the proposed distributions</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Mahmoud Abdelghaffar Mohamed Ahmed ; Supervised Mahmoud Riad Mahmoud , Rasha Mohamed Mandouh</note>
  <note>Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics </note>
  <note>Issued also as CD</note>
  <subject>
    <topic>Distributions pareto </topic>
  </subject>
  <subject>
    <topic>Pareto distribution and related distributions</topic>
  </subject>
  <subject>
    <topic>Related distributions</topic>
  </subject>
  <identifier type="uri">http://172.23.153.220/th.pdf</identifier>
  <location>
    <url>http://172.23.153.220/th.pdf</url>
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    <recordContentSource authority="marcorg">EG-GiCUC</recordContentSource>
    <recordCreationDate encoding="marc">190715</recordCreationDate>
    <recordChangeDate encoding="iso8601">20250223032328.0</recordChangeDate>
    <languageOfCataloging>
      <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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