Stochastic modeling of calibration drift in electrical meters

The drift in the calibration bias in an instrument can be modeled as a stochastic process, specifically, as the Wiener process. The probability distribution of this Wiener model can be found conditioned upon calibration at some time t₁. Bounds on the drift of the bias after calibration can be found as a function of time based upon an estimate of the parameter α, of the Wiener process. This parameter can be easily estimated based upon the collection of data calibration bias as a function of time. The statistical bounds on the calibration drift allow an instrument user to make his or her own choices as to the calibration interval based on the desired accuracy of the measurement