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| Justerad lådagram för sneda fördelningar× | Bootstrapinferens× | Medianabsolutavvikelse (MAD) – estimering× | |
|---|---|---|---|
| Ämnesområde | Statistik | Statistik | Statistik |
| Familj | Regression model | Regression model | Regression model |
| Ursprungsår≠ | 2008 | 1979 | 1974 |
| Upphovsperson≠ | Hubert & Vandervieren | Bradley Efron | Hampel (influence-curve treatment); classical robust statistics |
| Typ≠ | Robust outlier detection / descriptive visualization | Resampling-based inference | Robust scale estimator |
| Ursprungskälla≠ | Hubert, M. & Vandervieren, E. (2008). An Adjusted Boxplot for Skewed Distributions. Computational Statistics & Data Analysis, 52(12), 5186-5201. DOI ↗ | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ | Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗ |
| Alias | adjusted box plot, medcouple boxplot, skewness-adjusted boxplot, Düzeltilmiş Kutu Grafiği (Adjusted Boxplot) | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı | median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini |
| Närliggande | 5 | 5 | 5 |
| Sammanfattning≠ | The Adjusted Boxplot is a robust descriptive tool introduced by Hubert and Vandervieren (2008) that corrects the classical IQR-based boxplot for skewness using the medcouple statistic, reducing the false labelling of outliers in asymmetric data. | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. | Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result. |
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