Bayesian density estimation from grouped continuous data

Lambert, Philippe;Eilers, Paul H.C.
(2009) Computational Statistics & Data Analysis — Vol. 53, n° 4, p. 1388-1399 (2009)

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Abstract
Grouped data occur frequently in practice, either because of limited resolution of instruments, or because data have been summarized in relatively wide bins. A combination of the composite link model with roughness penalties is proposed to estimate smooth densities from such data in a Bayesian framework. A simulation study is used to evaluate the performances of the strategy in the estimation of a density, of its quantiles and first moments. Two illustrations are presented: the first one involves grouped data of lead concentration in the blood and the second one the number of deaths due to tuberculosis in The Netherlands in wide age classes.
Affiliations
  • UliègeInstitut des sciences humaines et sociales, Méthodes quantitatives en sciences sociales
  • University of UtrechtFaculty of Social and Behavioural Sciences
  • Institution iconUCLouvainAutre

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Lambert, P., & Eilers, P. H. C. (2009). Bayesian density estimation from grouped continuous data. Computational Statistics & Data Analysis, 53(4), 1388-1399. https://doi.org/10.1016/j.csda.2008.11.022 (Original work published 2009)