JSTOR Daily

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

On the Bias of Some Least-Squares Estimators of Variance in a General Linear Model

Watson (1955) investigated the performance of a regression analysis based on the assumption that the error covariance matrix is σ2γ when it is, in fact, σ2α. In ...
Simon Fraser University

SAS Technical Report R-103, Least-Squares Means in the Fixed-Effects General Linear Models

Defines the least-squares means for the fixed-effects general linear model. The report also discusses the use of least-squares means in lieu of class or subclass arithmetic means with unbalanced ...
Risk

Monitoring transmission of systemic risk: application of partial least squares structural equation modeling in financial stress testing

Regulators need a method that is versatile, is easy to use and can handle complex path models with latent (not directly observable) variables. In a first application of partial least squares ...