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In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. For example, the sample mean is a commonly used estimator of the population mean.
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Estimator | is a | rule for calculating an estimate of a given quantity based on observed data | 0.90 | text |
| Estimator | is a | method selected to obtain an estimate of an unknown parameter | 0.90 | text |
| Estimator | is a | type of decision rule | 0.90 | text |
| Estimator | is a | process of shooting arrows at the target | 0.90 | text |
| Estimator | is a | estimator whose sequence of estimates converge in probability to the quantity being estimated as the index | 0.90 | text |
| Estimator | is a | consistent estimator for parameter θ | 0.90 | text |
| Estimator | is a | same functional of the empirical distribution function as the true distribution function | 0.90 | text |
| Estimator | is a | consistent estimator whose distribution around the true parameter θ | 0.90 | text |
| Estimator | related to Asymptotic normality | An | 0.60 | section |
| Estimator | related to Asymptotic normality | Using | 0.60 | section |
| Estimator | related to Asymptotic normality | In | 0.60 | section |
| Estimator | related to Asymptotic normality | V/n | 0.60 | section |
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