We define the nagging predictor, which, instead of using bootstrapping to produce a series of i.i.d. predictors, exploits the randomness of neural network calibrations to provide a more stable and accurate predictor than is available from a single neural network run. Convergence results for the...

We define the nagging predictor, which, instead of using bootstrapping to produce a series of i.i.d. predictors, exploits the randomness of neural network calibrations to provide a more stable and accurate predictor than is available from a single neural network run. Convergence results for the...

The purpose of this paper is to validate the theoretical background of the specialized economic literature on financial performance of companies as a function of different capital structure determinants on the Romanian market. As such, the capital structure considered indicators are the short...

В работе предложена продуктивная методика адекватного регрессионного моделирования для систем управления эффективностью труда на основе анализа используемых...