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Finite mixture modeling of censored regression models
Umeå University, Faculty of Social Sciences, Umeå School of Business and Economics (USBE), Statistics.
Statistik, Örebro universitet.
2014 (English)In: Statistical papers, ISSN 0932-5026, E-ISSN 1613-9798, Vol. 55, no 3, 627-642 p.Article in journal (Refereed) Published
Abstract [en]

A finite mixture of Tobit models is suggested for estimation of regression models with a censored response variable. A mixture of models is not primarily adapted due to a true component structure in the population; the flexibility of the mixture is suggested as a way of avoiding non-robust parametrically specified models. The new estimator has several interesting features. One is its potential to yield valid estimates in cases with a high degree of censoring. The estimator is in a Monte Carlo simulation compared with earlier suggestions of estimators based on semi-parametric censored regression models. Simulation results are partly in favor of the proposed estimator and indicate potentials for further improvements.

Place, publisher, year, edition, pages
2014. Vol. 55, no 3, 627-642 p.
Keyword [en]
finite mixture models, censoring, Tobit, EM-algorithm
National Category
Probability Theory and Statistics
Research subject
URN: urn:nbn:se:umu:diva-67461DOI: 10.1007/s00362-013-0509-yISI: 000339339100004OAI: diva2:612016
Available from: 2013-03-19 Created: 2013-03-19 Last updated: 2014-09-01Bibliographically approved

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