Sequential estimation

In statistics, sequential estimation refers to estimation methods in sequential analysis where the sample size is not fixed in advance. Instead, data is evaluated as it is collected, and further sampling is stopped in accordance with a pre-defined stopping rule as soon as significant results are observed. The generic version is called optimal Bayesian Estimator. From that, the Kalman Filter (and its variants), the particle filter, the histogram filter and others can be derived.

See also

• Sequential Probability Ratio Test
• Testimator

References

• Thomas S. Ferguson (1967) Mathematical statistics: A decision theoretic approach., Academic Press. ISBN 0-12-253750-5
• Wald, Abraham (1947). Sequential Analysis. New York: John Wiley and Sons. ISBN 0-471-91806-7. See Dover reprint: ISBN 0-486-43912-7 {{cite book}}: ISBN / Date incompatibility (help)