Modern exploratory data analysis produces models that are not based on physical theory but that are consistent with pictures of the data. When both X and Y have error ...

Ordinary regression analysis is based on several statistical assumptions. One key assumption is that the errors are independent of each other. However, with time series data, the ordinary regression ...

The regression model with autocorrelated disturbances is as follows: In these equations, y t are the dependent values, x t is a column vector of regressor variables, is a column vector of structural ...

Abstract: In this paper, we exploit the properties of mean absolute error (MAE) as a loss function for the deep neural network (DNN) based vector-to-vector regression ...

Resampling approaches were the first techniques employed to compute a variance for the Gini coefficient. Various authors have demonstrated that estimates of the Gini ...

Properties of realized regression error terms are studied wherein they are treated as unknown parameters. Posterior distributions for individual realized error terms ...