Stochastic Measurement Procedures Based on Stationary Time Series

Abstract

Stochastic measurement procedures have been proposed and developed in several articles published in EQC. In contrast to the traditional measurement procedures that use the obsolete error propagation formula for taking into account measurement uncertainty, stochastic measurement procedures include the entire uncertainty of the measurement process in a natural and rational way. In this paper the concept of stochastic measurement procedure is extended to the case that the measurement process is given by a stochastic process or more precisely said by a time series. This case appears often for economic phenomena. In this paper, only the feasibility of such measurement procedures shall be demonstrated and the considerations are therefore restricted to some simple and rather unrealistic examples. In a realistic case an appropriate stochastic model must be developed following the rules of stochastic modelling.