1979/11/01 by Colin L. Mallows · 2 citations
Decision Sciences · Engineering · Mathematics · #Advanced Statistical Methods and Models #Advanced Statistical Process Monitoring #Fault Detection and Control Systems
paper · doi:10.1080/00031305.1979.10482689
openalex publication_date 1979/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
We describe several analyses in which robustness considerations have proved relevant. These examples exhibit the importance of (a) graphic displays as aids to formulating a preliminary model; (b) summary statistics that reduce the influence of outliers, that (c) give added opportunities of detecting relationships, and (d) are not unduly sensitive to granularity in the observations; and (e) techniques that pay due attention to anomalies in the data that superficially may appear to be negligible but that can obscure important effects. Finally, we make some general comments on the advantages and disadvantages of robust methodology.