Nonlinear prediction via Hermite transformation

Abstract

General prediction formulas involving Hermite polynomials are developed for time series expressed as a transformation of a Gaussian process. The prediction gains over linear predictors are examined numerically, demonstrating the improvement of nonlinear prediction.

Keywords

• gaussian transformation
• hermite polynomial
• nonlinear forecasting
• time series