Name
Abstract | ||
|---|---|---|
For general data, the number of complex solutions to the likelihood equations is constant and this number is called the (maximum likelihood) ML-degree of the model. In this article, we describe the special locus of data for which the likelihood equations have a solution in the model's singular locus. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jsc.2016.08.007 | J. Symb. Comput. |
Keywords | Field | DocType |
Maximum likelihood degree,Data singular locus,ML discriminant | Applied mathematics,Likelihood function,Likelihood-ratio test,Expectation–maximization algorithm,Mathematical analysis,Estimation theory,Restricted maximum likelihood,Maximum likelihood sequence estimation,Statistics,Mathematics,Estimating equations,Likelihood principle | Journal |
Volume | Issue | ISSN |
79 | P1 | 0747-7171 |
Citations | PageRank | References |
1 | 0.41 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emil Horobet | 1 | 39 | 3.07 |
| Jose Israel Rodriguez | 2 | 17 | 6.01 |