The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

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 ...

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 ...

Linear regression remains a cornerstone of statistical analysis, offering a framework for modelling relationships between a dependent variable and one or more independent predictors. Over the past ...

One aim of robust regression is to find estimators with high finite sample breakdown points. Although various robust estimators have been proposed in logistic regression models, their breakdown points ...