1. Université Saad Dahlab blida 1
  2. Faculté Des Sciences
  3. Département de Mathématique
  4. Mémoires de Master
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dc.contributor.authorAbbaci, Safaa-
dc.contributor.authorSaidi, Manel-
dc.contributor.authorRassoul, Abdelaziz (Promoteur)-
dc.date.accessioned2022-09-29T12:16:50Z-
dc.date.available2022-09-29T12:16:50Z-
dc.date.issued2022-07-
dc.identifier.urihttps://di.univ-blida.dz/jspui/handle/123456789/19532-
dc.descriptionill., Bibliogr. Cote: ma-510-135fr_FR
dc.description.abstractMissing data is a major issue in many applied problems. in our work we examine data that are missing and . the aims of multiple imputation in comparison to single imputation, we also studying the statistical inference by likelihood Maximum method for sample with missing data with Maximization-Expectation algorithm. Finally, we present the mains packages for imputation of missing data, and we applied the EM algorithm for Mixture Gaussian model Keywords: expectation maximization algorithm, missing data, imputation, maximum likelihood Methodfr_FR
dc.language.isoenfr_FR
dc.publisherUniversité Blida 1fr_FR
dc.subjectexpectation maximization algorithmfr_FR
dc.subjectmissing datafr_FR
dc.subjectimputationfr_FR
dc.subjectmaximum likelihood Methodfr_FR
dc.titleImputation of missing data and Inference by EM algorithmfr_FR
dc.typeThesisfr_FR
Collection(s) :Mémoires de Master

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