risks for effective credit risks management. The logistic lasso and ridge regression were employed. These methods are very …

Noisy markets need extensive descriptions that are noisy themselves, such as deep regression trees that capture many … models often do. Simple tools allow extraction of general and stock specific insightful information from such regression …

dimensional datasets. Our proposed five-step procedure for regression outlier detection entails a robust selection stage of the … most explicative variables, the estimation of a robust regression model based on the selected variables, and a criterion to …

order to model income, we apply distributional regression relating potentially each parameter of the conditional income …-term panel data from Germany, we build both mean and distributional regression models with the established 0.5 probability cutoff … income regression model into the distributional regression framework does not improve predictions further but has the …

predictions based on commonly provided regression output. Visual displays of quantitative information, including simple plots of …