Valid Model-Free Spatial Prediction

Backward Fokker-Planck equation for determining model valid prediction period

[1] A new concept, valid prediction period (VPP), is presented here to evaluate ocean (or atmospheric) model predictability. VPP is defined as the time period when the prediction error first exceeds a predetermined criterion (i.e., the tolerance level). It depends not only on the instantaneous error growth but also on the noise level, the initial error, and the tolerance level. The model predic...

Model-free vs. Model-based Volatility Prediction∗

The well-known ARCH/GARCH models for financial time series have been criticized of late for their poor performance in volatility prediction, i.e., prediction of squared returns.1 Focusing on three representative data series, namely a foreign exchange series (Yen vs. Dollar), a stock index series (the S&P500 index), and a stock price series (IBM), the case is made that financial returns may not ...

A Possibilistic Valid-Time Model

Information in databases can be imperfect and this imperfection has several forms and causes. In some cases, a single value should be stored, but it is (partially) unknown. The uncertainty about which value to store leads to the aforementioned imperfection. In temporal databases, uncertainty can arise, concerning which temporal notion needs to be stored. Because in temporal databases, temporal ...

Bayesian Prediction in Spatial Data Analysis

Determination of Model Valid Prediction Period Using the Backward Fokker-planck Equation

1. INTRODUCTION A practical question is commonly asked: How long is an ocean (or atmospheric) model valid since being integrated from its initial state? Or what is the model valid prediction period (VPP)? To answer this question, uncertainty in ocean (or atmospheric) models should be investigated. It is widely recognized that the uncertainty can be traced back to three factors [Lorenz, 1963; 19...