ScholarGate
Assistent

Sammenlign metoder

Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.

Mindste Trimmede Kvadraters (LTS) Regression×Robust ANOVA (Welch & Trimmed Mean)×
FagområdeStatistikStatistik
FamilieRegression modelRegression model
Oprindelsesår19841951
OphavspersonPeter J. RousseeuwWelch (1951); robust trimmed-mean approach popularised by Wilcox
TypeRobust linear regressionRobust one-way analysis of variance
Oprindelig kildeRousseeuw, P. J. (1984). Least Median of Squares Regression. Journal of the American Statistical Association, 79(388), 871-880. DOI ↗Welch, B. L. (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336. DOI ↗
AliasserLTS, least trimmed squares regression, trimmed least squares, robust regressionWelch ANOVA, trimmed-mean ANOVA, heteroscedastic one-way ANOVA, Robust ANOVA (Welch & Trimmed Mean)
Relaterede55
ResuméLeast Trimmed Squares is a robust linear regression method introduced by Peter J. Rousseeuw in 1984. Instead of fitting all residuals, it estimates the coefficients by minimising the sum of only the h smallest squared residuals, which gives it a breakdown point of up to 50% and reliable estimates on data heavily contaminated by outliers.Robust ANOVA compares the central tendency of three or more groups when the classical assumptions of normality and equal variances fail. It combines Welch's heteroscedasticity-adjusted statistic, introduced by Welch in 1951, with trimmed-mean tests advanced by Wilcox, giving reliable comparisons in the presence of outliers and unequal group spreads.
ScholarGateDatasæt
  1. v1
  2. 2 Kilder
  3. PUBLISHED
  1. v1
  2. 2 Kilder
  3. PUBLISHED

Gå til søgning Hent slides

ScholarGateSammenlign metoder: Least Trimmed Squares · Robust ANOVA. Hentet 2026-06-18 fra https://scholargate.app/da/compare