Model Fit and Diagnostic Statistics |
This section gathers the formulas for the statistics available in the MODEL, PLOT, and OUTPUT statements. The model to be fit is , and the parameter estimate is denoted by . The subscript denotes values for the th observation, the parenthetical subscript means that the statistic is computed by using all observations except the th observation, and the subscript indicates the th diagonal matrix entry. The ALPHA= option in the PROC REG or MODEL statement is used to set the value for the statistics.
Table 76.8 contains the summary statistics for assessing the fit of the model.
Definition or Formula |
|
---|---|
the number of observations |
|
the number of parameters including the intercept |
|
1 if there is an intercept, 0 otherwise |
|
the estimate of pure error variance from the SIGMA= |
|
the uncorrected total sum of squares for the dependent |
|
the total sum of squares corrected for the mean for the |
|
the error sum of squares |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
the sum of squares of (see Table 76.9) |
|
|
|
|
|
|
Table 76.9 contains the diagnostic statistics and their formulas; these formulas and further information can be found in Chapter 4, Introduction to Regression Procedures, and in the section Influence Statistics. Each statistic is computed for each observation.
Formula |
|
---|---|
PRED () |
|
RES () |
|
H () |
|
STDP |
|
STDI |
|
STDR |
|
LCL |
STDI |
LCLM |
STDP |
UCL |
STDI |
UCLM |
STDP |
STUDENT |
|
RSTUDENT |
|
COOKD |
|
COVRATIO |
|
DFFITS |
|
DFBETAS |
|
PRESS() |
|