consistent estimator

Statistical estimator converging in probability to a true parameter as sample size increases

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In statistics, a consistent estimator or asymptotically consistent estimator is an estimator—a rule for computing estimates of a parameter θ0—having the property that as the number of data points used increases indefinitely, the resulting sequence of estimates converges in probability to θ0. This means that the distributions of the estimates become more and more concentrated near the true value of the parameter being estimated, so that the probability of the estimator being arbitrarily close to θ0 converges to one.

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Source last edited July 10, 2026. AIDB refreshes this page daily.

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AIDB. (2026). consistent estimator (Q1782585). Retrieved from https://aidb.si/e/consistent-estimator-Q1782585