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Forecast Error Bounds Stochastic Simulation By Andrew P. Blake* 1. Introduction the effectiveness of an inflation assessing likely targeting in the real world. What can the National Institute model ...
Abstract:In this work, we extend the data-driven Itô stochastic differential equation (SDE) framework for the pathwise assessment of short-term forecast errors to account for the time-dependent upper ...
Abstract: In this work, we extend the data-driven Itô stochastic differential equation (SDE) framework for the pathwise assessment of short-term forecast errors to account for the time-dependent ...
Abstract: Motivated by recent advances in operational weather forecasting , we study the efficacy of low-precision arithmetic for climate simulations . We develop a framework to measure rounding error ...
AbstractMotivated by recent advances in operational weather forecasting , we study the efficacy of low-precision arithmetic for climate simulations . We develop a framework to measure rounding error ...
A time-dependent physical model whose initial condition is only approximately known can predict the evolving physical state to only within certain error bounds . In the prediction of weather, as well ...
to stochastically characterize the flow medium and to verify the model validity with specified confidence bounds . The updated model can then be employed to forecast future flow behavior. 1. Introduction Numerical ...
AbstractCurrent state-of-the art regional numerical weather forecasts are run at horizontal grid spacings of a few kilometers, which permits medium- to large-scale convective systems ...
A production management system contains many imprecise natures. The conventional deterministic and/or stochastic model in a computer integrated production management system (CIPMS) may not capture ...
, forward‐looking estimate of macroeconomic uncertainty, which equals the expected volatility of the forecast error for real GDP growth. Another benefit is that it allows us to make empirical predictions ...
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