values for the other observations in the sample. These extreme observations, or outliers, often have a large impact on the … applied researchers are usually aware of this the detection of outliers and their appropriate treatment is often dealt with in … for robust methods that can be used in the presence of outliers. Our paper intents to improve on this situation by …

of outliers by comparing a regression estimator that is robust to outliers (S-estimator), with another that is more e …

the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses … this, the detection of outliers and their appropriate treatment is often dealt with in a rather sloppy manner. One reason … the presence of outliers. Our paper intents to improve on this situation by presenting a highly robust method for …

In the robust statistics literature, a wide variety of models have been devel- oped to cope with outliers in a rather …

In the robust statistics literature, a wide variety of models have been developed to cope with outliers in a rather …

the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses … this, the detection of outliers and their appropriate treatment is often dealt with in a rather sloppy manner. One reason … the presence of outliers. Our paper intents to improve on this situation by presenting a highly robust method for …

the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses … this, the detection of outliers and their appropriate treatment is often dealt with in a rather sloppy manner. One reason … the presence of outliers. Our paper intents to improve on this situation by presenting a highly robust method for …

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 … methods resist only some specific types of outliers and turn out to be ineffective under alternative scenarios. In this …

the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses … this, the detection of outliers and their appropriate treatment is often dealt with in a rather sloppy manner. One reason … the presence of outliers. Our paper intents to improve on this situation by presenting a highly robust method for …