Please use this identifier to cite or link to this item: https://doi.org/10.1016/0167-9473(95)00050-X
DC FieldValue
dc.titleOn singular multivariate normal distribution and its applications
dc.contributor.authorKwong, K.-S.
dc.contributor.authorIglewicz, B.
dc.date.accessioned2011-04-18T08:42:06Z
dc.date.available2011-04-18T08:42:06Z
dc.date.issued1996
dc.identifier.citationKwong, K.-S., Iglewicz, B. (1996). On singular multivariate normal distribution and its applications. Computational Statistics and Data Analysis 22 (3) : 271-285. ScholarBank@NUS Repository. https://doi.org/10.1016/0167-9473(95)00050-X
dc.identifier.issn01679473
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/21419
dc.description.abstractThe methods of evaluating the singular multivariate normal distribution have been commonly applied even though the complete analytical proofs are not found. Recently, those evaluation methods are shown to have some errors. In this paper we present a new approach with a complete proof for evaluating the exact two-sided percentage points of a standardized m-variate normal distribution with a singular negative product correlation structure for m = 3 and with a singular negative equi-correlated structure for m ≥ 3. The results are then applied to modify the existing procedures for estimating joint confidence intervals for multinomial proportions and for determining sample sizes. By extending the results from the multivariate normal distribution to the multivariate t-distribution with the corresponding singular correlation structure, we obtain the corrected two-sided exact critical values for the Analysis of Means for m = 4, 5.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/0167-9473(95)00050-X
dc.sourceScopus
dc.subjectAnalysis of Means
dc.subjectConfidence intervals
dc.subjectEqui-correlated
dc.subjectMultinomial distribution
dc.subjectSample size estimation
dc.typeArticle
dc.contributor.departmentECONOMICS & STATISTICS
dc.description.doi10.1016/0167-9473(95)00050-X
dc.description.sourcetitleComputational Statistics and Data Analysis
dc.description.volume22
dc.description.issue3
dc.description.page271-285
dc.description.codenCSDAD
dc.identifier.isiutA1996UX53700004
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