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In this paper we consider several estimators for the variogram: the classical estimator due to Matheron, a robust estimator proposed by Cressie & Hawkins, and two highly robust estimators introduced by Rousseeuw in the context of scale estimation. It will ...
A non-parametric method of distribution estimation for univariate data is presented. The idea is to adapt the smoothing spline procedure used in regression to the estimation of distributions via a scatterplot smoothing of theempirical distribution function ...
This note addresses the problem of robust multiobjective filtering for discrete time-delay systems with mixed stochastic and deterministic uncertainties, in addition to unmodeled nonlinearities. A procedure is developed for the design of linear and exponen ...
An application to antenna optimization of bayesian network density of probability estimators is presented. This technique is very usefull for optimizations where abig number of parameters, multiple solutions and local minima increase the likelihood to conv ...
In the context of spatial statistics, the classical variogram estimator proposed by Matheron is not robust against outliers in the data, nor is Cressie and Hawkins' estimator. Therefore, we suggest the use of a variogram estimator based on a highly robust ...
In this paper we derive the change-of-variance function of M-estimators of scale under general contamination, thereby extending the formula in Hampel et al. (1986). We say that an M-estimator is B-robust if its influence function is bounded, and we call it ...
We address the question of how to characterize the outliers that may appear when matching two views of the same scene. The match is performed by comparing the difference of the two views at a pixel level, aiming at a better registration of the images. When ...
We consider unicast equation based rate control defined as follows. A source adjusts its rate primarily at loss events to f(p) where p is an estimator of loss event ratio. Function f is typically the loss-throughput formula of a TCP source. In absence of l ...
The estimation of cumulative distributions is classically performed using the empirical distribution function. This estimator has excellent properties but is lacking continuity. Smooth versions of the empirical distribution function have been obtained by k ...
The authors achieve robust estimation of parametric models through the use of weighted maximum likelihood techniques. A new estimator is proposed and its good properties illustrated through examples. Ease of implementation is an attractive property of the ...
