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Modelling Task Completion Data with Inverse Gaussian Mixtures
Author(s) -
Desmond A. F.,
Chapman G. R.
Publication year - 1993
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2986178
Subject(s) - inverse gaussian distribution , gaussian , statistics , mathematics , computer science , econometrics , chemistry , mathematical analysis , distribution (mathematics) , computational chemistry
SUMMARY Whitmore introduced mixtures of inverse Gaussian distributions and fitted them to several data sets involving duration phenomena. In this paper we model task completion data from a large automobile plant in southern Ontario, with a mixed inverse Gaussian distribution. The mixing is over a parameter that can be naturally identified with the intensity with which the work crew approaches its task. It is found that, depending on the nature of the task, the mixed distribution may provide an improvement over the familiar pure inverse Gaussian distribution. A secondary consideration is the study of asymptotic likelihood inference for such mixtures.