5 citations · 10 across the 7 of their papers we have counts for
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Quantile-respectful density estimation based on the Harrell-Davis quantile estimator
Andrey Akinshin
Traditional density and quantile estimators are often inconsistent with each other. Their simultaneous usage may lead to inconsistent results. To address this issue, we propose a n…
Weighted quantile estimators
Andrey Akinshin
In this paper, we consider a generic scheme that allows building weighted versions of various quantile estimators, such as traditional quantile estimators based on linear interpola…
Finite-sample Rousseeuw-Croux scale estimators
Andrey Akinshin
The Rousseeuw-Croux , scale estimators and the median absolute deviation can be used as consistent estimators for the standard deviation under nor…
Quantile absolute deviation
Andrey Akinshin
The median absolute deviation (MAD) is a popular robust measure of statistical dispersion. However, when it is applied to non-parametric distributions (especially multimodal, discr…
Finite-sample bias-correction factors for the median absolute deviation based on the Harrell-Davis quantile estimator and its trimmed modification
Andrey Akinshin
The median absolute deviation is a widely used robust measure of statistical dispersion. Using a scale constant, we can use it as an asymptotically consistent estimator for the sta…
Trimmed Harrell-Davis quantile estimator based on the highest density interval of the given width
Andrey Akinshin
Traditional quantile estimators that are based on one or two order statistics are a common way to estimate distribution quantiles based on the given samples. These estimators are r…