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In non-parametric statistics, the Theil–Sen estimator is a method for robustly fitting a line to sample points in the plane (simple linear regression) by choosing the median of the slopes of all lines through pairs of points. It has also been called Sen's slope estimator, slope selection, the single median method, the Kendall robust line-fit method, and the Kendall–Theil robust line. It is named after Henri Theil and Pranab K. Sen, who published papers on this method in 1950 and 1968 respectively, and after Maurice Kendall because of its relation to the Kendall tau rank correlation coefficient.

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  • Theil–Sen estimator (en)
  • Оценочная функция Тейла – Сена (ru)
  • 泰尔-森估算 (zh)
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  • 泰尔-森估算(英語:Theil–Sen estimator)是非参数统计中一种拟合直线的稳健模型,名称来源于荷兰计量经济学家与美国统计学家。 假设有二维样本数据(xi,yi),泰尔-森估算是指所有样本点对所形成的斜率(yj − yi)/(xj − xi)的中位数m。当拟合直线的斜率m确定后,可再由yi − mxi的中位数确定拟合直线的截距。 泰尔-森估算不易受离群值影响。对于偏态分布或异方差的数据,泰尔-森估算的准确度远高于非稳健的简单线性回归,而对于正态分布数据而言其与非稳健模型相比也有着相当的统计功效。 (zh)
  • In non-parametric statistics, the Theil–Sen estimator is a method for robustly fitting a line to sample points in the plane (simple linear regression) by choosing the median of the slopes of all lines through pairs of points. It has also been called Sen's slope estimator, slope selection, the single median method, the Kendall robust line-fit method, and the Kendall–Theil robust line. It is named after Henri Theil and Pranab K. Sen, who published papers on this method in 1950 and 1968 respectively, and after Maurice Kendall because of its relation to the Kendall tau rank correlation coefficient. (en)
  • В непараметрической статистике существует метод для робастного множества точек (простая линейная регрессия), в котором выбирается медиана наклонов всех прямых, проходящих через пары точек выборки на плоскости. Метод называется оценочной функцией Тейла — Сена, оценочной функцией Сена коэффициента наклона, выбором наклона, методом одной медианы, методом Кендалла робастного приближения прямой и робастной прямой Кендалла — Тейла. Метод назван именами Анри Тейла и Пранаба К. Сена, опубликовавшими статьи об этом методе в 1950 и 1968 соответственно, а также именем Мориса Кендалла. (ru)
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