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Deconvolving multivariate kernel density estimates from contaminated associated observations

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1 Author(s)
Masry, E. ; Dept. of Electr. & Comput. Eng., Univ. of California, La Jolla, CA, USA

We consider the estimation of the multivariate probability density function f(x1,...,xp) of X1,...,Xp of a stationary positively or negatively associated (PA or NA) random process {Xi}i=1 from noisy observations. Both ordinary smooth and super smooth noise are considered. Quadratic mean and asymptotic normality results are established.

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Information Theory, IEEE Transactions on  (Volume:49 ,  Issue: 11 )