Optimal quantization for mixed distributions

Authors

Mrinal Kanti Roychowdhury, The University of Texas Rio Grande ValleyFollow

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.

Comments

Original published version available at https://doi.org/10.14321/realanalexch.46.2.0451

Recommended Citation

Roychowdhury, Mrinal Kanti. 2021. “Optimal Quantization for Mixed Distributions.” Real Analysis Exchange 46 (2): 451–84. https://doi.org/10.14321/realanalexch.46.2.0451

Publication Title

Real Analysis Exchange

DOI

10.14321/realanalexch.46.2.0451