Name
Abstract | ||
|---|---|---|
The development of an approach for obtaining statistical inferences about nonobservable processes that influence a processy(cdot)which can be observed directly and which is assumed to be a mixture of continuous and discontinuous components is continued. The approach is based on probability-measure transformations and consists of finding the conditional probability of a nonobservable event in terms of the prior probability of that event and a functional of the observationsy(cdot). The topics studied include optimal filtering, smoothing, and prediction estimates of the nonobservable process;M-ary hypothesis testing; performance lower-bounds; and stochastic control. |
Year | DOI | Venue |
|---|---|---|
1978 | 10.1109/TIT.1978.1055824 | Information Theory, IEEE Transactions |
Keywords | Field | DocType |
Decision procedures,Estimation,Martingales | Discrete mathematics,Applied mathematics,Mathematical optimization,Martingale (probability theory),Conditional probability,Filter (signal processing),Smoothing,Statistical inference,Prior probability,Statistical hypothesis testing,Mathematics,Stochastic control | Journal |
Volume | Issue | ISSN |
24 | 1 | 0018-9448 |
Citations | PageRank | References |
3 | 2.51 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vaca, M. | 1 | 8 | 4.58 |
| Snyder, Donald L. | 2 | 363 | 175.26 |