Estimation I

Abstract

Estimation is the process of extracting information about the value of a parameter, given some data related to the parameter. In general the data are assumed to be some random sample from a “population”, and the parameter is a global characteristic of the population. In an engineering context, we are often interested in interpreting the output of a sensor or multiple sensors: real sensors give inexact measurements for a variety of reasons: Electrical noise – robot strain gauge; Sampling error – milling machine encoder (see figure 1); Calibration error – thermocouple Quantization/Shot noise – CCD (see figure 2) We seek suitable mathematical tools with which to model and manipulate uncertainties and errors. This is provided by probability theory – the “calculus of uncertainty”.

Cite this paper

@inproceedings{Reid2010EstimationI, title={Estimation I}, author={I . D . Reid}, year={2010} }