For a robust estimation of the parameter, we expect the estimated parameter does not change significantly with respect to a data perturbation. In another word, the influence function is bounded for a robust estimation.
Robust parameter estimation with a small bias against heavy ...
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In this paper we consider robust parameter estimation based on a certain cross entropy and divergence. The robust estimate is defined as the minimizer of ...
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Abstract: A constructive approach to robust parameter estimation that carries over naturally to the nonparametric estimation is presented.
This paper contains a new approach toward a theory of robust estimation; it treats in detail the asymptotic theory of estimating a location parameter for ...
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[PDF] Robust Parameter Estimation in Computer Vision - People @EECS
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Estimation techniques in computer vision applications must estimate accurate model pa- rameters despite small-scale noise in the data, occasional large-scale ...
Robust estimators coupled with the geometric constraint that hold between images of a scene can determine model parameters in the presence of a large number of ...
Sep 27, 2019 · Abstract:This paper considers the problem of robustly estimating the parameters of a heavy-tailed multivariate distribution when the ...
Sep 22, 2022 · One candidate for quantifying robustness would be to look at the relative standard deviations of the estimation error under a misspecified model.
Robust statistics are statistics that maintain their properties even if the underlying distributional assumptions are incorrect.
Jun 18, 2024 · Parameter estimation algorithms typically rely on ex- ploiting information about the structure of the system along with the available input and ...