Tests for outliers in the inverse Gaussian distribution, with application to first hitting time models

Stogiannis, D; Caroni, C

dc.contributor.author	Stogiannis, D	en
dc.contributor.author	Caroni, C	en
dc.date.accessioned	2014-03-01T02:14:47Z
dc.date.available	2014-03-01T02:14:47Z
dc.date.issued	2012	en
dc.identifier.issn	00949655	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30117
dc.subject	first hitting time	en
dc.subject	inverse Gaussian	en
dc.subject	likelihood ratio	en
dc.subject	outliers	en
dc.title	Tests for outliers in the inverse Gaussian distribution, with application to first hitting time models	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/00949655.2010.527843	en
heal.identifier.secondary	http://dx.doi.org/10.1080/00949655.2010.527843	en
heal.publicationDate	2012	en
heal.abstract	The inverse Gaussian (IG) distribution is often applied in statistical modelling, especially with lifetime data. We present tests for outlying values of the parameters (μ, λ) of this distribution when data are available from a sample of independent units and possibly with more than one event per unit. Outlier tests are constructed from likelihood ratio tests for equality of parameters. The test for an outlying value of λ is based on an F-distributed statistic that is transformed to an approximate normal statistic when there are unequal numbers of events per unit. Simulation studies are used to confirm that Bonferroni tests have accurate size and to examine the powers of the tests. The application to first hitting time models, where the IG distribution is derived from an underlying Wiener process, is described. The tests are illustrated on data concerning the strength of different lots of insulating material. © 2012 Taylor and Francis Group, LLC.	en
heal.journalName	Journal of Statistical Computation and Simulation	en
dc.identifier.doi	10.1080/00949655.2010.527843	en
dc.identifier.volume	82	en
dc.identifier.issue	1	en
dc.identifier.spage	73	en
dc.identifier.epage	80	en