summary:The properties of the regular linear model are well known (see [1], Chapter 1). In this paper the situation where the vector of the first order parameters is divided into two parts (to the vector of the useful parameters and to the vector of the nuisance parameters) is considered. It will be shown how the BLUEs of these parameters will be changed by constraints given on them. The theory will be illustrated by an example from the practice
summary:Unknown parameters of the covariance matrix (variance components) of the observation vector ...
summary:Nonsensitiveness regions for estimators of linear functions, for confidence ellipsoids, for ...
summary:Dispersion of measurement results is an important parameter that enables us not only to char...
summary:The properties of the regular linear model are well known (see [1], Chapter 1). In this pape...
summary:A large number of parameters in regression models can be serious obstacle for processing and...
summary:A large number of parameters in regression models can be serious obstacle for processing and...
summary:The estimation procedures in the multiepoch (and specially twoepoch) linear regression model...
summary:The estimation procedures in the multiepoch (and specially twoepoch) linear regression model...
summary:Bad conditioned matrix of normal equations in connection with small values of model paramete...
summary:Bad conditioned matrix of normal equations in connection with small values of model paramete...
summary:Nowadays, the algorithm most frequently used for determination of the estimators of paramete...
summary:Nowadays, the algorithm most frequently used for determination of the estimators of paramete...
summary:In weakly nonlinear regression model a weakly nonlinear hypothesis can be tested by linear m...
summary:In weakly nonlinear regression model a weakly nonlinear hypothesis can be tested by linear m...
summary:Unknown parameters of the covariance matrix (variance components) of the observation vector ...
summary:Unknown parameters of the covariance matrix (variance components) of the observation vector ...
summary:Nonsensitiveness regions for estimators of linear functions, for confidence ellipsoids, for ...
summary:Dispersion of measurement results is an important parameter that enables us not only to char...
summary:The properties of the regular linear model are well known (see [1], Chapter 1). In this pape...
summary:A large number of parameters in regression models can be serious obstacle for processing and...
summary:A large number of parameters in regression models can be serious obstacle for processing and...
summary:The estimation procedures in the multiepoch (and specially twoepoch) linear regression model...
summary:The estimation procedures in the multiepoch (and specially twoepoch) linear regression model...
summary:Bad conditioned matrix of normal equations in connection with small values of model paramete...
summary:Bad conditioned matrix of normal equations in connection with small values of model paramete...
summary:Nowadays, the algorithm most frequently used for determination of the estimators of paramete...
summary:Nowadays, the algorithm most frequently used for determination of the estimators of paramete...
summary:In weakly nonlinear regression model a weakly nonlinear hypothesis can be tested by linear m...
summary:In weakly nonlinear regression model a weakly nonlinear hypothesis can be tested by linear m...
summary:Unknown parameters of the covariance matrix (variance components) of the observation vector ...
summary:Unknown parameters of the covariance matrix (variance components) of the observation vector ...
summary:Nonsensitiveness regions for estimators of linear functions, for confidence ellipsoids, for ...
summary:Dispersion of measurement results is an important parameter that enables us not only to char...