Forecast Bias Correction: A Second Order Method

Details Forecast Bias Correction: A Second Order Method Forecast Bias Correction: A Second Order Method

2010-11-05

arxiv.org/abs/1011.1508v1

Computer Science

Computational Engineering, Finance, and Science

27 Pages, 3 figures, 8 tables

Scientific paper

The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.

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