What question did this study set out to answer?

This research explores the robustness of minimum distance (MD) functionals against contamination and compares it with other functionals.

The "Automatic" Robustness of Minimum Distance Functionals

View Full Paper

Ask AI

Bookmark

This research explores the robustness of minimum distance (MD) functionals against contamination and compares it with other functionals.
Evaluated minimum distance functionals defined by various distances and their sensitivity to $$-contamination.
Compared the breakdown points of MD functionals with Fisher-consistent and equivariant functionals.
Applied findings to simple location models, multivariate settings, and semiparametric contexts.
MD functional showed at least half the best possible breakdown point against $$-contamination.
In invariant settings, MD functional achieved the best attainable breakdown points compared to equivariant functionals.
Hilbertian distance metrics revealed MD functional having the smallest sensitivity to contamination among Fisher-consistent functionals.

No takes yet. Share an insight, caveat, or question.

Randomized trial demonstrates the robustness of minimum distance functionals, indicating their reliability in statistical analysis.

Donoho et al. (1988) studied this question.

View Full Paper

Ask AI

Bookmark