School of Mathematical and Statistical Sciences Faculty Publications and Presentations
Document Type
Article
Publication Date
11-8-2021
Abstract
The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability distribution by a discrete distribution. Mixed distributions are an exciting new area for optimal quantization. In this paper, we have determined the optimal sets of n -means, the n th quantization errors, and the quantization dimensions of different mixed distributions. Besides, we have discussed whether the quantization coefficients for the mixed distributions exist. The results in this paper will give a motivation and insight into more general problems in quantization for mixed distributions.
Recommended Citation
Mrinal Kanti Roychowdhury. "OPTIMAL QUANTIZATION FOR MIXED DISTRIBUTIONS." Real Anal. Exchange 46 (2) 451 - 484, 2021. https://doi.org/10.14321/realanalexch.46.2.0451
Publication Title
Real Analysis Exchange
DOI
10.14321/realanalexch.46.2.0451
Comments
Original published version available at https://doi.org/10.14321/realanalexch.46.2.0451