and variations in the operation data. Then stochastic modeling of the combustion process is done by a Gaussian process …

The theoretical relationship between the prediction variance of a Gaussian process model (GPM) and its mean square … estimation of Gaussian process models when the simulated data observations contain measurement noise. In particular, this work … Gaussian process model using stochastic simulations are preserved when the signal-to-noise ratio in the data is larger than 10 …

and its time-adaptiveness. This model based on the warped Gaussian process (WGP), which handles the non … Gaussian process (GP), then the non-Gaussian uncertainty associated with the wind power can be predicted in a standard GP …

A new nonparametric estimator of the local Hurst function of a multifractional Gaussian process based on the increment …

Let {X(t):t∈[0,∞)} be a centered stationary Gaussian process. We study the exact asymptotics of P(sups∈[0,T]X(s)>u), as …