estimator
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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.
~23 min read
Article
21 sectionsContents
- Discussion
- Definition
- Quantified properties
- Error
- Mean squared error
- Sampling deviation
- Variance
- Bias
- Unbiased
- Relationships among the quantities
- Example
- Behavioral properties
- Consistency
- Fisher consistency
- Asymptotic normality
- Efficiency
- Robustness
- See also
- References
- Further reading
- External links
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.
There are point and interval estimators. The point estimators yield single-valued results. This is in contrast to an interval estimator, where the result would be a range of plausible values. "Single value" does not necessarily mean "single number", but includes vector valued or function valued estimators.