M.D. I. Estimation via Unconstrained Convex Programming.
TEXAS UNIV AT AUSTIN CENTER FOR CYBERNETIC STUDIES
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A method is presented for obtaining minimum discrimination information M.D.I. estimates of probability distributions. This involves using an extremal principal and, viewing M.D.I. estimation in a dual convex programming framework. The resulting dual convex program is unconstrained and involves only exponential and linear terms, and hence is easily solved. This approach makes M.D.I. estimation computationally efficient and reduces the time and cost of obtaining such estimates.
- Statistics and Probability