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Inference for grouped data with a truncated skew-Laplace distribution

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Rubio, F. J. and Steel, Mark F. J.. (2011) Inference for grouped data with a truncated skew-Laplace distribution. Computational Statistics & Data Analysis, Vol.55 (No.12). pp. 3218-3231. ISSN 0167-9473

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.csda.2011.06.002

Abstract

The skew-Laplace distribution has been used for modelling particle size with point observations. In reality, the observations are truncated and grouped (rounded). This must be formally taken into account for accurate modelling, and it is shown how this leads to convenient closed-form expressions for the likelihood in this model. In a Bayesian framework, "noninformative" benchmark priors, which only require the choice of a single scalar prior hyperparameter, are specified. Conditions for the existence of the posterior distribution are derived when rounding and various forms of truncation are considered. The main application focus is on modelling microbiological data obtained with flow cytometry. However, the model is also applied to data often used to illustrate other skewed distributions, and it is shown that our modelling compares favourably with the popular skew-Student models. Further examples with simulated data illustrate the wide applicability of the model.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Q Science > QR Microbiology
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Bayesian statistical decision theory, Flow cytometry -- Data processing, Glass fibers -- Data processing, Rounding (Numerical analysis), Monte Carlo method
Journal or Publication Title: Computational Statistics & Data Analysis
Publisher: Elsevier BV
ISSN: 0167-9473
Date: 2011
Volume: Vol.55
Number: No.12
Number of Pages: 14
Page Range: pp. 3218-3231
Identification Number: 10.1016/j.csda.2011.06.002
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
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URI: http://wrap.warwick.ac.uk/id/eprint/38121

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