Name
Abstract | ||
|---|---|---|
Extends the maximum entropy information-theoretic density estimation method to provide a technique which guarantees that the resulting density is unimodal. The method inputs data in the form of moment or quantile constraints and consequently can handle both data-derived and non-data-derived information |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1109/18.382035 | IEEE Transactions on Information Theory |
Keywords | Field | DocType |
maximum entropy methods,parameter estimation,probability,data-derived information,information-theoretic approach,maximum entropy,moment constraints,nondata-derived information,probability density distribution,quantile constraints,unimodal density estimation | Information theory,Density estimation,Unimodality,Combinatorics,Quantile,Principle of maximum entropy,Estimation theory,Probability density function,Mathematics | Journal |
Volume | Issue | ISSN |
41 | 3 | 0018-9448 |
Citations | PageRank | References |
5 | 0.83 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| P. L. Brockett | 1 | 5 | 0.83 |
| A. Charnes | 2 | 271 | 145.50 |
| Paick, K.H. | 3 | 5 | 0.83 |