Generalized unscented transformation for forecasting non-Gaussian processes
{{output}}
The observations of linear and nonlinear physical processes are subject to random errors, which can be represented by a wide variety of probability distributions. In contrast, most estimation and inference techniques rely on a Gaussian assumption, which may li... ...
