ABSTRACT
Chapter 1 explained the processing of static measurement data. It discussed the recognition of systematic errors and negligent errors, the estimation of statistical characteristics of random errors, the precision analysis of physical quantities, etc. Chapter 2 studied various parametric representations of signals from dynamic measurement targets. It laid the foundation for constructing regression models of information to be estimated. In this chapter, we will focus on how to estimate unknown parameters in regression models. Since the goodness of a regression model has a very important influence on the precision of parameter estimation, model evaluation and optimization will also be studied.
