Results 91 to 100 of about 478,225 (113)

The strong uniform convergence of multivariate variable kernel estimates

Canadian Journal of Statistics, 1986
AbstractWe show that sup, completely as, where f is a uniformly continuous density on are independent random vectors with common density f, and fn is the variable kernel estimateHere Hni is the distance between Xi and its kth nearest neighbour, K is a given density satisfying some regularity conditions, and k is a sequence of integers with the property
Devroye, Luc, Penrod, Clark S.
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Strong uniform convergence of the recursive regression estimator under f-mixing conditions

Metrika, 2004
Suppose the observations (X i , Y i ) taking values in R d ×R, are φ-mixing. Compared with the i.i.d. case, some known strong uniform convergence
Li Wang, Han-Ying Liang
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Strong uniform convergence of density estimators on compact Euclidean manifolds

Statistics & Probability Letters, 1993
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Hendriks, H.W.M., Janssen, J.H.M., Ruymgaart, F.H.   +2 more
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Strong uniform convergence of density estimators on spheres

Journal of Statistical Planning and Inference, 1989
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On estimate of convergence rate to Ito’s equation. The case of uniform strong intermixing

Random Operators and Stochastic Equations, 1999
The authors consider the Cauchy problem on \([0,T]\) \[ {{dX_{\varepsilon}}\over{dt}}=\alpha(t,X_{\varepsilon})+ \sigma(t,X_{\varepsilon})\eta(t/\varepsilon), \qquad X_{\varepsilon}(0)=x_0, \] where \(\varepsilon>0\) is a small parameter, \(\eta(t)\), \(t\geq 0\), is a stationary stochastic process with zero mean that satisfies the uniform strong ...
Bondarev, B. V., Polshkov, Yu. N.
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Strong Uniform Convergence Rates for Some Robust Equivariant Nonparametric Regression Estimates for Mixing Processes

International Statistical Review / Revue Internationale de Statistique, 1991
Summary: We prove the strong uniform consistency of some robust equivariant nonparametric regression estimates, based on kernel weights and on nearest neighbor with kernel weights, for strongly and uniform strongly processes. Strong uniform convergence rates for these estimates are obtained. Applications to robust nonparametric autoregression are given.
Boente, Graciela, Fraiman, Ricardo
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Rate of strong uniform convergence of k-NN density estimates

Journal of Statistical Planning and Inference, 1983
The author uses recent results of \textit{W. Stute} [Ann. Probab. 10, 86-107 and 414-422 (1982; Zbl 0489.60038 and Zbl 0493.62040, respectively)] on the oscillation behavior of empirical processes to derive the rate of strong uniform convergence of the kth-nearest neighbor density estimator \(f_ n(x)\) to the true density f(x) on a closed interval J on
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Uniform strong convergence results for the conditional kaplan-meier estimator and its quantiles

Communications in Statistics - Theory and Methods, 1996
We consider a fixed design model in which the responses are possibly right censored. The aim of this paper is to establish some important almost sure convergence properties of the Kaplan-Meier type estimator for the lifetime distribution at a given covariate value. We also consider the corresponding quantile estimator and obtain a modulus of continuity
Ingrid Van Keilegom, Noël Veraverbeke
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A note on uniform strong convergence of bivariate density estimates

Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1974
In this paper we consider a class of estimates of a bivariate density function f based on an independent sample of size n. Under the assumption that f is uniformly continuous, the uniform strong consistency of such estimates was first proved by Nadaraya (1970) for a large class of kernel functions.
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