When Outliers are Significant: Weighted Linear Regression

Methods for weighted regression that incorporate significant outliers

Outliers are often mischievous. They have the potential to disrupt an otherwise simple process of regression by introducing themselves as data that is as equally important as the rest, often skewing the fitted model. A straightforward approach is to use outlier detection methods to remove them from the dataset prior to fitting a model. But this has its caveats. Sometimes outliers may be significant and are …

data science linear linear regression outliers programming regression statistics weighted-regression