The theory of Minimum Norm Quadratic Estimators for estimating variances and covariances is applied to show that some commonly used estimators of covariances in time series models are easily derived using the above principle. In applying the theory MINQE, it is observed that no unbiased estimator exists in the class of invariant quadratics.jackknife estimator minimum norm quadratic estimator autocovariance estimation
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
The Minimum Norm Quadratic Unbiased Invariant Estimator of the estimable linear function of the unkn...
Multivariate linear models with ellipsoidal restrictions are introduced for the modelling of semipar...
summary:The least squres invariant quadratic estimator of an unknown covariance function of a stocha...
A class of martingale estimating functions is convenient and plays an important role for inference f...
Estimation of variance components in several classes of quadratic estimators is considered. It inclu...
We write a linear model in the form Y=Xβ+Uξ, where β is an unknown parameter and ξ is a hypothetical...
AbstractThis paper deals with the problem of optimal quadratic unbiased estimation for statistical m...
This paper investigates the estimation of covariance matrices in multivariate mixed models. Some suf...
AbstractThe paper consists of two parts. The first part deals with solutions to some optimization pr...
For the usual MANOVA model ............, Khatri (1979) obtained necessary and sufficient conditions ...
AbstractThis paper investigates the estimation of covariance matrices in multivariate mixed models. ...
We consider nonnegative invariant quadratic estimation of variance components and prove that if ther...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
[[abstract]]© 1993 INFORMS - Many commonly used estimators of the variance of the sample mean from a...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
The Minimum Norm Quadratic Unbiased Invariant Estimator of the estimable linear function of the unkn...
Multivariate linear models with ellipsoidal restrictions are introduced for the modelling of semipar...
summary:The least squres invariant quadratic estimator of an unknown covariance function of a stocha...
A class of martingale estimating functions is convenient and plays an important role for inference f...
Estimation of variance components in several classes of quadratic estimators is considered. It inclu...
We write a linear model in the form Y=Xβ+Uξ, where β is an unknown parameter and ξ is a hypothetical...
AbstractThis paper deals with the problem of optimal quadratic unbiased estimation for statistical m...
This paper investigates the estimation of covariance matrices in multivariate mixed models. Some suf...
AbstractThe paper consists of two parts. The first part deals with solutions to some optimization pr...
For the usual MANOVA model ............, Khatri (1979) obtained necessary and sufficient conditions ...
AbstractThis paper investigates the estimation of covariance matrices in multivariate mixed models. ...
We consider nonnegative invariant quadratic estimation of variance components and prove that if ther...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
[[abstract]]© 1993 INFORMS - Many commonly used estimators of the variance of the sample mean from a...
The paper consists of two parts. The first part deals with solutions to some optimization problems. ...
The Minimum Norm Quadratic Unbiased Invariant Estimator of the estimable linear function of the unkn...
Multivariate linear models with ellipsoidal restrictions are introduced for the modelling of semipar...