<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-27T15:35:30Z</responseDate><request verb="GetRecord" identifier="oai:docta.ucm.es:20.500.14352/50117" metadataPrefix="mods">https://docta.ucm.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:docta.ucm.es:20.500.14352/50117</identifier><datestamp>2023-08-27T08:19:54Z</datestamp><setSpec>com_20.500.14352_14</setSpec><setSpec>col_20.500.14352_15</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
   <mods:name>
      <mods:namePart>Landaburu Jiménez, María Elena</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Pardo Llorente, Leandro</mods:namePart>
   </mods:name>
   <mods:extension>
      <mods:dateAvailable encoding="iso8601">2023-06-20T09:39:11Z</mods:dateAvailable>
   </mods:extension>
   <mods:extension>
      <mods:dateAccessioned encoding="iso8601">2023-06-20T09:39:11Z</mods:dateAccessioned>
   </mods:extension>
   <mods:originInfo>
      <mods:dateIssued encoding="iso8601">2006</mods:dateIssued>
   </mods:originInfo>
   <mods:identifier type="issn">0368-492X</mods:identifier>
   <mods:identifier type="doi">10.1108/03684920610662467</mods:identifier>
   <mods:identifier type="uri">https://hdl.handle.net/20.500.14352/50117</mods:identifier>
   <mods:identifier type="officialurl">http://www.ingentaconnect.com/content/mcb/067/2006/00000035/00000005/art00009</mods:identifier>
   <mods:identifier type="relatedurl">http://www.ingentaconnect.com/</mods:identifier>
   <mods:abstract>Purpose - Proposes a test of goodness-of-fit with composite null hypotheses and weights in the classes based on weighted (h, p)-divergences. Design/methodology/approach - The weighted (h, p)-divergence between an empirical distribution and the probability of the estimated model is here investigated for large simple random samples.
Findings - The unknown parameters of the model are estimated using minimum (h, p)-divergences estimators with weights as studied in previous works by the authors.
Originality/value - Research makes an important contribution to (h, P)-divergences and their applications in statistical and other areas.</mods:abstract>
   <mods:accessCondition type="useAndReproduction">metadata only access</mods:accessCondition>
   <mods:titleInfo>
      <mods:title>Weighted (h,theta)-divergences in goodness-of-fit with composite null hypotheses</mods:title>
   </mods:titleInfo>
   <mods:genre>journal article</mods:genre>
</mods:mods></metadata></record></GetRecord></OAI-PMH>