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In statistics, the method of estimating equations is a way of specifying how the parameters of a statistical model should be estimated. This can be thought of as a generalisation of many classical methods—the method of moments, least squares, and maximum likelihood—as well as some recent methods like M-estimators.
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Estimating equations | is a | way of specifying how the parameters of a statistical model should be estimated | 0.90 | text |
| Estimating equations | related to References | Godambe | 0.60 | section |
| Estimating equations | related to References | Estimating Functions | 0.60 | section |
| Estimating equations | related to References | New York | 0.60 | section |
| Estimating equations | related to References | Oxford University Press | 0.60 | section |
| Estimating equations | related to References | ISBN | 0.60 | section |
| Estimating equations | related to References | Heyde | 0.60 | section |
| Estimating equations | related to References | Christopher | 0.60 | section |
| Estimating equations | related to References | Quasi-Likelihood | 0.60 | section |
| Estimating equations | related to References | Its Application | 0.60 | section |
| Estimating equations | related to References | General Approach | 0.60 | section |
| Estimating equations | related to References | Optimal Parameter Estimation | 0.60 | section |
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