Posts / Preprint announcement: 'Finite-sample Rousseeuw-Croux scale estimators'


Recently, I published a preprint of a paper ‘Finite-sample Rousseeuw-Croux scale estimators’. It’s based on a series of my research notes.

The paper preprint is available on arXiv: arXiv:2209.12268 [stat.ME]. The paper source code is available on GitHub: AndreyAkinshin/paper-frc. You can cite it as follows:

Abstract:

The Rousseeuw-Croux $S_n$, $Q_n$ scale estimators and the median absolute deviation $\operatorname{MAD}_n$ can be used as consistent estimators for the standard deviation under normality. All of them are highly robust: the breakdown point of all three estimators is $50\%$. However, $S_n$ and $Q_n$ are much more efficient than $\operatorname{MAD}_n$: their asymptotic Gaussian efficiency values are $58\%$ and $82\%$ respectively compared to $37\%$ for $\operatorname{MAD}_n$. Although these values look impressive, they are only asymptotic values. The actual Gaussian efficiency of $S_n$ and $Q_n$ for small sample sizes is noticeably lower than in the asymptotic case.

The original work by Rousseeuw and Croux (1993) provides only rough approximations of the finite-sample bias-correction factors for $S_n,\, Q_n$ and brief notes on their finite-sample efficiency values. In this paper, we perform extensive Monte-Carlo simulations in order to obtain refined values of the finite-sample properties of the Rousseeuw-Croux scale estimators. We present accurate values of the bias-correction factors and Gaussian efficiency for small samples ($n \leq 100$) and prediction equations for samples of larger sizes.

Relevant blog posts

Here is the full list of the relevant blog posts:

BibTeX reference

@article{akinshin2022frc,
  title = {Finite-sample Rousseeuw-Croux scale estimators},
  author = {Akinshin, Andrey},
  year = {2022},
  month = {9},
  publisher = {arXiv},
  doi = {10.48550/arXiv.2209.12268},
  url = {https://arxiv.org/abs/2209.12268}
}

References (1)