
doi: 10.2307/1403649
Summary: The method of least squares ranks as one of the most commonly used methods for estimating the relation between a set of variables on the conditional expected value of another variable. Ordinary Least Squares (OLS) relies on several assumptions, which when violated may not yield robust estimates. We pose alternative ways to view this model. In particular we study Gini regression which is equivalent to OLS when the assumptions hold, and is more robust when the assumptions fail. Gini regression can also be used to test the validity of the assumptions.
Gini regression, Linear regression; mixed models, Gini correlation, absolute deviation, Probabilistic methods, stochastic differential equations, robust estimation, Nonparametric inference, ordinary least squares
Gini regression, Linear regression; mixed models, Gini correlation, absolute deviation, Probabilistic methods, stochastic differential equations, robust estimation, Nonparametric inference, ordinary least squares
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 72 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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