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On a Gaussian process related to multivariate probability density estimation

Published online by Cambridge University Press:  24 October 2008

B. W. Silverman
Affiliation:
Statistical Laboratory, University of Cambridge

Extract

The multivariate Gaussian process with the same variance/covariance structure as the multivariate kernel density estimator in Euclidean space of dimension d is considered. An exact result is obtained for the limit in probability of the maximum of the normalized process. In addition weak and strong bounds are placed on the asymptotic behaviour of the maximum of the process over a multidimensional interval which is allowed to increase as the sample size increases. All the bounds obtained on the process are

Only the uniform continuity of the underlying density is assumed; the conditions on the kernel are also mild.

Type
Research Article
Copyright
Copyright © Cambridge Philosophical Society 1976

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References

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