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Remedian：适用于大型数据集的稳健汇总方法AI 解读

It is often assumed that to compute a robust estimator on n data values one needs at least n storage elements (contrary to the sample average, that may be calculated with an updating mechanism). This is one of the main reasons why robust estimators are seldom used for large data sets and why they are not included in most statistical packages. We introduce a new estimator that takes up little storage space, investigate its statistical properties, and provide an example on…

Remedian：适用于大型数据集的稳健平均方法AI 解读

It is often assumed that to compute a robust estimator on n data values one needs at least n storage elements (contrary to the sample average, that may be calculated with an updating mechanism). This is one of the main reasons why robust estimators are seldom used for large data sets and why they are not included in most statistical packages. We introduce a new estimator that takes up little storage space, investigate its statistical properties, and provide an example on…

回归分位数及相关经验过程的强一致性AI 解读

The strong consistency of regression quantile statistics (Koenker and Bassett [4]) in linear models with iid errors is established. Mild regularity conditions on the regression design sequence and the error distribution are required. Strong consistency of the associated empirical quantile process (introduced in Bassett and Koenker [1]) is also established under analogous conditions. However, for the proposed estimate of the conditional distribution function of Y, no…