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Bayesian analysis of frequency count data

Author
Font, M.; Puig, X.; Ginebra, J.
Type of activity
Journal article
Journal
Journal of statistical computation and simulation
Date of publication
2013-02
Volume
83
Number
2
First page
229
Last page
246
DOI
https://doi.org/10.1080/00949655.2011.600311 Open in new window
Repository
http://hdl.handle.net/2117/14798 Open in new window
Abstract
The zero truncated inverse Gaussian–Poisson model, obtained by first mixing the Poisson model assuming its expected value has an inverse Gaussian distribution and then truncating the model at zero, is very useful when modelling frequency count data. A Bayesian analysis based on this statistical model is implemented on the word frequency counts of various texts, and its validity is checked by exploring the posterior distribution of the Pearson errors and by implementing posterior predictive con...
Citation
Font, M.; Puig, X.; Ginebra, J. Bayesian analysis of frequency count data. "Journal of statistical computation and simulation", 2011, p. 1-18.
Keywords
Poisson mixture, Sichel model, diversity, inverse Gaussian, population size, species frequency, textual data, vocabulary distribution
Group of research
ADBD - Analysis of Complex Data for Business Decisions

Participants