Estimating bias error distributions

In this article we formulate a general methodology for estimating the bias error distribution of a device in a measurement domain from less accurate m easurements when a minimal number of standard values (typically no more tha n two values) are available. A new perspective is that the bias error distr ibution can be found as a solution of an intrinsic functional equation in a domain. Based on this theory, the scaling- and translation-based methods f or determining the bias error distribution are developed. These methods are applicable to virtually any device as long as the bias error distribution of the device can be sufficiently described by a power series (a polynomial ) or a Fourier series in a domain. These methods were validated through com putational simulations and laboratory calibration experiments for a number of different devices.