summary:The paper deals with an optimal estimation of the quadratic function $\bold{\beta'D\beta}$, where $\beta \in \Cal R^k, \bold D$ is a known $k \times k$ matrix, in the model $\bold{Y, X\beta, \sigma^2I}$. The distribution of $\bold Y$ is assumed to be symmetric and to have a finite fourth moment. An explicit form of the best unbiased estimator is given for a special case of the matrix $\bold X$
summary:The paper deals with modified minimax quadratic estimation of variance and covariance compon...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In nonlinear regression models an approximate value of an unknown parameter is frequently at...
summary:The paper deals with an optimal estimation of the quadratic function $\bold{\beta'D\beta}$, ...
summary:The paper deals with the linear model with uncorrelated observations. The dispersions of the...
summary:The paper deals with the linear model with uncorrelated observations. The dispersions of the...
summary:The paper deals with the estimation of unknown vector parameter of mean and scalar parameter...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:The paper deals with the estimation of the unknown vector parameter of the mean and the para...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:The paper deals with the estimation of the unknown vector parameter of the mean and the para...
summary:The paper deals with modified minimax quadratic estimation of variance and covariance compon...
AbstractThe variance of a quadratic function of the random variables in a linear model is minimized ...
summary:The paper deals with modified minimax quadratic estimation of variance and covariance compon...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In nonlinear regression models an approximate value of an unknown parameter is frequently at...
summary:The paper deals with an optimal estimation of the quadratic function $\bold{\beta'D\beta}$, ...
summary:The paper deals with the linear model with uncorrelated observations. The dispersions of the...
summary:The paper deals with the linear model with uncorrelated observations. The dispersions of the...
summary:The paper deals with the estimation of unknown vector parameter of mean and scalar parameter...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:In the paper an explicit expression for the Bayes invariant quadratic unbiased estimate of t...
summary:The paper deals with the estimation of the unknown vector parameter of the mean and the para...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:In the paper four types of estimations of the linear function of the variance components are...
summary:The paper deals with the estimation of the unknown vector parameter of the mean and the para...
summary:The paper deals with modified minimax quadratic estimation of variance and covariance compon...
AbstractThe variance of a quadratic function of the random variables in a linear model is minimized ...
summary:The paper deals with modified minimax quadratic estimation of variance and covariance compon...
summary:In the paper necessary and sufficient conditions for the existence and an explicit expressio...
summary:In nonlinear regression models an approximate value of an unknown parameter is frequently at...