Melola Discovery

← Melola Discovery

Open access Jurnal

Bayesian inference for Pareto distribution with prior conjugate and prior non conjugate

Jurnal Matematika, Statistika dan Komputasi · Vol. 16 No. 3 (2020) · pp. 382–390

DOI
10.20956/jmsk.v16i3.8019
ISSN
2614-8811, 1858-1382
Published
2020-04-28
Publisher
Department of Mathematics, Hasanuddin University
Language
en
License
creativecommons.org/licenses/by/4.0

Abstract

The purpose of this study is to determine the best estimator for estimating the shape parameters of the Pareto distribution with the known scale parameter. Estimation of these parameters is done by using the Gamma distribution as the prior distribution of the conjugate and the Uniform distribution as the non-conjugate prior distribution. A comparison of the two prior distributions is done through simulation studies with various sample sizes. The best estimator net is a method that produces the smallest posterior variance, absolute bias, and Bayes confidence interval. This study proves that the Bayes estimator by using the prior conjugate distribution produces all indicators of the goodness of the model with a smaller value than the non-conjugate prior distribution. Thus it can be concluded that the estimator with prior conjugate will produce a better predictive value than prior non-conjugate.

Keywords

Collaboration network of the authors

18 authors · 37 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Muhammadiyah Madiun
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Maiyastri MaiyastriAffiliation unknown3
Frilianda WulandariAffiliation unknown2
Rudiyanto RudiyantoAffiliation unknown2
Lilis Harianti HasibuanAffiliation unknown2
Muhammad Qolbi ShobriUniversitas Muhammadiyah Madiun2
SRI WAHYUNIAffiliation unknown1
Fery MurtiningrumAffiliation unknown1
Melinda NoerAffiliation unknown1
Sisca WulandariAffiliation unknown1
Izzati Rahmi HGAffiliation unknown1
Aulia ZuardinAffiliation unknown1
Ridho SaputraAffiliation unknown1
Alvi Khairin NisaAffiliation unknown1
Nia RamadhaniAffiliation unknown1
Mawanda AlmuhayarAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Bayesian inference for Pareto distribution with prior conjugate and prior non conjugate</dc:title>
	<dc:creator xml:lang="en">YANUAR, Ferra</dc:creator>
	<dc:creator xml:lang="en">Saputri, Cici</dc:creator>
	<dc:creator xml:lang="en">Devianto, Dodi </dc:creator>
	<dc:subject xml:lang="en">Pareto distribution</dc:subject>
	<dc:subject xml:lang="en">posterior variance</dc:subject>
	<dc:subject xml:lang="en">absolute bias</dc:subject>
	<dc:subject xml:lang="en">Bayes confidence interval</dc:subject>
	<dc:description xml:lang="en">The purpose of this study is to determine the best estimator for estimating the shape   parameters of the Pareto distribution with the known  scale parameter. Estimation of these parameters is done by using the Gamma distribution as the prior distribution of the conjugate and the Uniform distribution as the non-conjugate prior distribution. A comparison of the two prior distributions is done through simulation studies with various sample sizes. The best estimator net is a method that produces the smallest posterior variance, absolute bias, and Bayes confidence interval. This study proves that the Bayes estimator by using the prior conjugate distribution produces all indicators of the goodness of the model with a smaller value than the non-conjugate prior distribution. Thus it can be concluded that the estimator with prior conjugate will produce a better predictive value than prior non-conjugate.</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2020-04-28</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/8019</dc:identifier>
	<dc:identifier>10.20956/jmsk.v16i3.8019</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 16 No. 3 (2020): JMSK, MAY, 2020; 382-390</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/8019/pdf</dc:relation>
	<dc:relation>10.20956/j.v16i3.8019.g5103</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2020 Jurnal Matematika, Statistika dan Komputasi</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>