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Generalized Maximum Spacing Estimation for Multivariate Observations
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2015 (English)In: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 42, no 4, p. 1092-1108Article in journal (Refereed) Published
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Abstract [en]

In this paper, the maximum spacing method is considered for multivariate observations. Nearest neighbour balls are used as a multidimensional analogue to univariate spacings. A class of information-type measures is used to generalize the concept of maximum spacing estimators. Weak and strong consistency of these generalized maximum spacing estimators are proved both when the assigned model class is correct and when the true density is not a member of the model class. An example of the generalized maximum spacing method in model validation context is discussed.

Place, publisher, year, edition, pages
2015. Vol. 42, no 4, p. 1092-1108
Keywords [en]
divergence measures, maximum spacing estimation, nearest neighbour balls, strong consistency, ak consistency
National Category
Mathematical Analysis Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-116106DOI: 10.1111/sjos.12153ISI: 000368246600012PubMedID: 24843434OAI: oai:DiVA.org:umu-116106DiVA, id: diva2:901498
Available from: 2016-02-08 Created: 2016-02-08 Last updated: 2018-03-15Bibliographically approved

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