• Bernoulli
  • Volume 12, Number 1 (2006), 143-156.

A continuous Gaussian approximation to a nonparametric regression in two dimensions

Andrew V. Carter

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Estimating the mean in a nonparametric regression on a two-dimensional regular grid of design points is asymptotically equivalent to estimating the drift of a continuous Gaussian process on the unit square. In particular, we provide a construction of a Brownian sheet process with a drift that is almost the mean function in the nonparametric regression. This can be used to apply estimation or testing procedures from the continuous process to the regression experiment as in Le~Cam's theory of equivalent experiments. Our result is motivated by first looking at the amount of information lost in binning the data in a density estimation problem.

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Bernoulli Volume 12, Number 1 (2006), 143-156.

First available in Project Euclid: 28 February 2006

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asymptotic equivalence of experiments density estimation nonparametric regression


Carter, Andrew V. A continuous Gaussian approximation to a nonparametric regression in two dimensions. Bernoulli 12 (2006), no. 1, 143--156.

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