Summary In empirical studies often the values of some variables for some observations are much larger or smaller than the values for the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses. Conclusions based...

In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses - conclusions based on a sample with and without these units...

In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses - conclusions based on a sample with and without these units...

In the robust statistics literature, a wide variety of models have been developed to cope with outliers in a rather large number of scenarios. Nevertheless, a recurrent problem for the empirical implementation of these estimators is that optimization algorithms generally do not perform well when...

In empirical studies often the values of some variables for some observations are much larger or smaller than the values for the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses. Conclusions based on a...

In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses – conclusions based on a sample with and without these...

In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses – conclusions based on a sample with and without these...

In regression analysis, the presence of outliers in the dataset can strongly distort the classical least-squares estimator and lead to unreliable results. To deal with this, several robust-to-outliers methods have been proposed in the statistical literature. In Stata, some of these methods are...