point estimator - meaning and definition. What is point estimator
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What (who) is point estimator - definition

PARAMETER ESTIMATION VIA SAMPLE STATISTICS
Point estimator; Point estimate
  • Point estimation and confidence interval estimation.

Point estimation         
In statistics, point estimation involves the use of sample data to calculate a single value (known as a point estimate since it identifies a point in some parameter space) which is to serve as a "best guess" or "best estimate" of an unknown population parameter (for example, the population mean). More formally, it is the application of a point estimator to the data to obtain a point estimate.
Estimator         
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USED IN MATHEMATICAL STATISTICS TO DETERMINE AN ESTIMATED VALUE
Efficiency bound; Restricted estimate; Unrestricted estimate; Asymptotically unbiased; Estimators; Asymptotically normal estimator; Parameter estimate; Universal estimator; Estimated value; Statistical estimate; Estimate (statistics)
·noun One who estimates or values; a valuer.
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USED IN MATHEMATICAL STATISTICS TO DETERMINE AN ESTIMATED VALUE
Efficiency bound; Restricted estimate; Unrestricted estimate; Asymptotically unbiased; Estimators; Asymptotically normal estimator; Parameter estimate; Universal estimator; Estimated value; Statistical estimate; Estimate (statistics)
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.

Wikipedia

Point estimation

In statistics, point estimation involves the use of sample data to calculate a single value (known as a point estimate since it identifies a point in some parameter space) which is to serve as a "best guess" or "best estimate" of an unknown population parameter (for example, the population mean). More formally, it is the application of a point estimator to the data to obtain a point estimate.

Point estimation can be contrasted with interval estimation: such interval estimates are typically either confidence intervals, in the case of frequentist inference, or credible intervals, in the case of Bayesian inference. More generally, a point estimator can be contrasted with a set estimator. Examples are given by confidence sets or credible sets. A point estimator can also be contrasted with a distribution estimator. Examples are given by confidence distributions, randomized estimators, and Bayesian posteriors.