. The research presented involved developing algorithms for the implementation of linear regression for estimating CVaR as a … linear regression can be reduced to minimizing the Rockafellar error function with linear programming. The theoretical basis …. Alternatively, a two-stage procedure based on the decomposition theorem can be used for CVaR linear regression with both sets of …

for regression models. In this paper we propose a new scenario generation method for linear regression used in performance … properties of linear regression models and cluster based resampling. Secondly, our scenario generation method is more robust to … model "overfitting" by utilising a multiple of linear regression functions, hence our scenarios are more reliable. Finally …

sustainability in Ethiopia using a yearly time series data that lasts from 1980 to 2016. A log-linear regression model was used, and …

In the literature, although many studies are describing the structural break in the linear regression model with time … some approaches used to determine the structural break in a linear regression equation based on cross-sectional data was …

for regression models. In this paper we propose a new scenario generation method for linear regression used in performance … properties of linear regression models and cluster based resampling. Secondly, our scenario generation method is more robust to … model "overfitting" by utilising a multiple of linear regression functions, hence our scenarios are more reliable. Finally …