Pour savoir comment effectuer et gérer un dépôt de document, consultez le « Guide abrégé – Dépôt de documents » sur le site Web de la Bibliothèque. Pour toute question, écrivez à corpus@ulaval.ca.
 

Publication :
Sampling a two dimensional matrix

bul.description.provenanceeb bde spb autorité-manquante : Ewane Ebouelefr
bul.rights.dateAccepPubl2020-04-04fr
bul.rights.periodeEmbargoP0Mfr
bul.rights.typeDatedatePublicationfr
dc.contributor.authorRivest, Louis-Paul
dc.contributor.authorEwane Ebouele, Sergio
dc.date.accessioned2020-06-24T12:39:18Z
dc.date.available2020-06-24T12:39:18Z
dc.date.issued2020-04-04
dc.description.abstractA new sampling design for populations whose units can be arranged as an matrix is proposed. The sample must satisfy some constraints: row and column sample sizes are set in advance. The proposed sampling method gives the same selection probability to all the sample matrices that satisfy the constraints. Three algorithms to select a sample uniformly in the feasible set are presented: an exact algorithm based on the multivariate hypergeometric distribution, an MCMC algorithm, and the cube method. Their performances are evaluated using Monte Carlo simulations. The designs for sampling elements in a given row or a given column are investigated and the single inclusion and joint selection probabilities under the proposed design are evaluated. Several variance estimators are proposed for the Horvitz–Thompson estimator of the population mean of the survey variable and their performances are compared in a Monte Carlo study. A numerical example dealing with a creel survey of fishermen found at 9 sites over 36 days is presented.fr
dc.identifier.doi10.1016/j.csda.2020.106971fr
dc.identifier.issn0167-9473fr
dc.identifier.urihttp://hdl.handle.net/20.500.11794/39558
dc.languageengfr
dc.publisherElsevierfr
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectBalanced samplingfr
dc.subjectCreel surveyfr
dc.subjectCube methodfr
dc.subjectMultivariate hypergeometric distributionfr
dc.subjectMonte Carlo Markov Chainfr
dc.subject.rvmÉchantillonnage (Statistique)fr
dc.subject.rvmMatricesfr
dc.titleSampling a two dimensional matrixfr
dc.typearticle de recherche
dc.type.legacyCOAR1_1::Texte::Périodique::Revue::Contribution à un journal::Article::Article de recherchefr
dcterms.bibliographicCitationComputational statistics and data analysis, Vol. 149 (2020)fr
dspace.accessstatus.time2024-03-23 18:01:45
dspace.entity.typePublication
relation.isAuthorOfPublicationae194257-3a07-4a0a-b82c-0e98c34f0e3f
relation.isAuthorOfPublication.latestForDiscoveryae194257-3a07-4a0a-b82c-0e98c34f0e3f
relation.isResourceTypeOfPublication4c433ef5-3937-4530-8252-cca17d715747
relation.isResourceTypeOfPublication.latestForDiscovery4c433ef5-3937-4530-8252-cca17d715747
rioxxterms.project.funder-nameCanada First Research Excellence Fundfr
rioxxterms.project.funder-nameNatural Sciences and Engineering Research Council of Canadafr
rioxxterms.versionProof (P)fr
rioxxterms.version-of-recordhttps://doi.org/10.1016/j.csda.2020.106971fr

Fichiers

Bundle original
Voici les éléments 1 - 1 sur 1
En cours de chargement...
Vignette d'image
Nom :
Rivest&Ebouele2020.pdf
Taille :
581.01 KB
Format :
Adobe Portable Document Format