The paper gives a self-contained account of linear least squares regression when the errors have an arbitrary error covariance matrix. The finite sample size case is ...

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 ...

The process of using past cost information to predict future costs is called cost estimation. While many methods are used for cost estimation, the least-squares regression method of cost estimation is ...

Linear regression-based quantitative trait loci/association mapping methods such as least squares commonly assume normality of residuals. In genetics studies of plants or animals, some quantitative ...