This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related nonlinearly to the target variable. In kernel ridge regression, the observed predictor variables are mapped nonlinearly into a high-dimensional space, where estimation of the...

Non-homogeneous regression models are widely used to statistically post-process numerical ensemble weather prediction models. Such regression models are capable of forecasting full probability distributions and correct for ensemble errors in the mean and variance. To estimate the corresponding...

Introducing the Brownian motion in the way of Einstein and Wiener we find the connection between a Wiener Process and the Heat Diffusion PDE.We solve the PDE analytically for some boundary conditions and then use the connection to the Wiener Process to solve more complex BVP's using Monte Carlo...