Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Оценка на основе медианного абсолютного отклонения (MAD)× | Регрессия методом обыкновенных наименьших квадратов (ОНМК)× | Тест перестановок (рандомизация)× | |
|---|---|---|---|
| Область≠ | Статистика | Эконометрика | Статистика |
| Семейство | Regression model | Regression model | Regression model |
| Год появления≠ | 1974 | 2019 | 2005 |
| Автор метода≠ | Hampel (influence-curve treatment); classical robust statistics | Wooldridge (textbook treatment); classical least squares | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Тип≠ | Robust scale estimator | Linear regression | Nonparametric resampling test |
| Основополагающий источник≠ | Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Другие названия | median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Связанные | 5 | 5 | 5 |
| Сводка≠ | 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. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). | The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value. |
| ScholarGateНабор данных ↗ |
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