The Hat Matrix in Regression and ANOVA

摘要: Abstract In least-squares fitting it is important to understand the influence which a data y value will have on each fitted value. A projection matrix known as hat contains this information and, together with Studentized residuals, provides means of identifying exceptional points. This approach also simplifies calculations involved in removing point, and requires only simple modifications preferred numerical algorithms.