DFFITS
In statistics, DFFIT and DFFITS ("difference in fit(s)") are diagnostics meant to show how influential a point is in a linear regression, first proposed in 1980. DFFIT is the change in the predicted value for a point, obtained when that point is left out of the regression: DFFIT = y ^ i − y ^ i ( i ) {\displaystyle {\text{DFFIT}}={\widehat {y}}_{i}-{\widehat {y}}_{i(i)}} where y ^ i {\displaystyle {\widehat {y}}_{i}} and y ^ i ( i ) {\displaystyle {\widehat {y}}_{i(i)}} are the prediction for point i with and without point i included in the regression.