Sieve estimator
In statistics, sieve estimators are a class of non-parametric estimator which use progressively more complex models to estimate an unknown high-dimensional function as more data becomes available, with the aim of asymptotically reducing error towards zero as the amount of data increases. This method is generally attributed to Ulf Grenander.
See also
External links
- Stuart Geman, Chii-Ruey Hwang. "Nonparametric Maximum Likelihood Estimation by the Method of Sieves" (PDF). The Annals of Statistics, Vol. 10, No. 2 (Jun., 1982), pp. 401-414.
- "Sieve Estimation" (PDF). Archived from the original (PDF) on September 2, 2006.
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