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Least Upper Bound for the Covariance Matrix of a Generalized Least Squares Estimator in Regression with Applications to a Seemingly Unrelated Regression Model and a ...

In a general normal regression model, this paper first derives the least upper bound (LUB) for the covariance matrix of a generalized least squares estimator (GLSE) relative to the covariance matrix ...
JSTOR Daily

Adaptive Estimators of a Mean Matrix: Total Least Squares versus Total Shrinkage

This is a preview. Log in through your library . Abstract An unknown constant matrix M is observed with additive random error. The basic problem considered is to ...
Simon Fraser University

Example 5.5: Approximate Standard Errors

The NLP procedure provides a variety of ways for estimating parameters in nonlinear statistical models and for obtaining approximate standard errors and covariance matrices for the estimators. These ...
Simon Fraser University

Example 45.2: Iteratively Reweighted Least Squares

The NLIN procedure is suited to methods that make the weight a function of the parameters in each iteration since the _WEIGHT_ variable can be computed with program statements. The NOHALVE option is ...