Inference for grouped data with a truncated skew-Laplace distribution
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.
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- H. Schneeweiss & J. Komlos & A. Ahmad, 2010. "Symmetric and asymmetric rounding: a review and some new results," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(3), pages 247-271, September.
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- Carmen Fernandez & Mark F J Steel, 1998. "Reference priors for the general location-scale model," ESE Discussion Papers 23, Edinburgh School of Economics, University of Edinburgh.
- Ferreira, Jose T.A.S. & Steel, Mark F.J., 2006. "A Constructive Representation of Univariate Skewed Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 823-829, June.
- Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "A Constructive Representation of Univariate Skewed Distributions," Econometrics 0403002, EconWPA.
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