Confidence intervals for median absolute deviations

Abstract

The median absolute deviation (MAD) is a robust measure of scale that is simple to implement and easy to interpret. Motivated by this, we introduce interval estimators of the MAD to make reliable inferences for dispersion for a single population and ratios and differences of MADs for comparing two populations. Our simulation results show that the coverage probabilities of the intervals are very close to the nominal coverage for a variety of distributions. We have used partial influence functions to investigate the robustness properties of the difference and ratios of independent MADs.

Reference

Chandima N P G Arachchige, Luke A Prendergast “Confidence intervals for median absolute deviations” (2019) arXiv:1910.00229

@Article{arachchige2019,
  title = {Confidence intervals for median absolute deviations},
  url = {http://arxiv.org/abs/1910.00229},
  abstract = {The median absolute deviation (MAD) is a robust measure of scale that is simple to implement and easy to interpret. Motivated by this, we introduce interval estimators of the MAD to make reliable inferences for dispersion for a single population and ratios and differences of MADs for comparing two populations. Our simulation results show that the coverage probabilities of the intervals are very close to the nominal coverage for a variety of distributions. We have used partial influence functions to investigate the robustness properties of the difference and ratios of independent MADs.},
  urldate = {2020-07-14},
  journal = {arXiv:1910.00229 [math, stat]},
  author = {Arachchige, Chandima N P G and Prendergast, Luke A},
  month = {nov},
  year = {2019},
  note = {arXiv: 1910.00229},
  arxiv = {1910.00229},
  keywords = {Mathematics - Statistics Theory}
}