  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. Mixtures of probability
distributions, also known as mixed distributions, are an exciting new area for
optimal quantization. In this paper, we investigate the optimal quantization
for three different mixed distributions generated by uniform distributions
associated with probability vectors.
