1. A Bayesian model for multinomial sampling with misclassified data.
- Author
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Ruiz, M., Girón, F.J., Pérez, C.J., Martín, J., and Rojano, C.
- Subjects
- *
BAYESIAN analysis , *DIFFERENTIAL equations , *GIBBS' equation , *ALGORITHMS , *NOISE , *EMPIRICAL research - Abstract
In this paper the issue of making inferences with misclassified data from a noisy multinomial process is addressed. A Bayesian model for making inferences about the proportions and the noise parameters is developed. The problem is reformulated in a more tractable form by introducing auxiliary or latent random vectors. This allows for an easy-to-implement Gibbs sampling-based algorithm to generate samples from the distributions of interest. An illustrative example related to elections is also presented. [ABSTRACT FROM AUTHOR]
- Published
- 2008
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