Quantization of Prior Probabilities for Hypothesis Testing

Kush R. Varshney; Lav R. Varshney

doi:10.1109/tsp.2008.928164

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arXiv · 0805.4338

Quantization of Prior Probabilities for Hypothesis Testing

Kush R. Varshney·Lav R. Varshney

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Abstract

Bayesian hypothesis testing is investigated when the prior probabilities of the hypotheses, taken as a random vector, are quantized. Nearest neighbor and centroid conditions are derived using mean Bayes risk error as a distortion measure for quantization. A high-resolution approximation to the distortion-rate function is also obtained. Human decision making in segregated populations is studied assuming Bayesian hypothesis testing with quantized priors.

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Kush R. Varshney, Lav R. Varshney. 2008-05-28. Quantization of Prior Probabilities for Hypothesis Testing. https://doi.org/10.1109/tsp.2008.928164

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