Uncertainty of the design and covariance matrices in linear statistical model
The aim of the paper is to determine an influence of uncertainties in design and covariance matrices on estimators in linear regression model.
Underparametrization of weakly nonlinear regression models
A large number of parameters in regression models can be serious obstacle for processing and interpretation of experimental data. One way how to overcome it is an elimination of some parameters. In some cases it need not deteriorate statistical properties of estimators of useful parameters and can help to interpret them. The problem is to find conditions which enable us to decide whether such favourable situation occurs.