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 ...

This section illustrates how to solve some ordinary least-squares problems and generalizations of those problems by formulating them as transformation regression problems. One problem involves finding ...

This is a preview. Log in through your library . Abstract Least squares solution of F= PG with respect to positive semidefinite symmetric P is considered,a new necessary and sufficient condition for ...

In a multivariate regression model, the errors in different equations may be correlated. In this case the efficiency of the estimation may be improved by taking these cross-equation correlations into ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

Scientists in Spain have implemented recursive least squares (RLS) algorithms for anomaly detection in PV systems and have found they can provide “more realistic and meaningful assessment” than ...