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Table 55.5 contains the summary statistics for assessing the fit of the model.
Table 55.5: Formulas and Definitions for Model Fit Summary StatisticsDefinition or Formula | |
n | the number of observations |
p | the number of parameters including the intercept |
i | 1 if there is an intercept, 0 otherwise |
the estimate of pure error variance from the SIGMA= option or from fitting the full model | |
SST0 | the uncorrected total sum of squares for the dependent variable |
SST1 | the total sum of squares corrected for the mean for the dependent variable |
SSE | the error sum of squares |
MSE | |
R2 | |
ADJRSQ | |
AIC | |
BIC | |
CP (Cp) | |
GMSEP | [( MSE(n+1)(n-2))/(n(n-p-1))] = [1/n] Sp(n+1)(n-2) |
JP (Jp) | [(n+p)/n] MSE |
PC | [(n+p)/(n-p)] (1 - R2) = Jp ( [n/( SSTi)] ) |
PRESS | the sum of squares of predri (see Table 55.6) |
RMSE | |
SBC | n ln( [ SSE/n] ) + p ln(n) |
SP (Sp) | [ MSE/(n-p-1)] |
Table 55.6 contains the diagnostic statistics and their formulas; these formulas and further information can be found in Chapter 3, "Introduction to Regression Procedures," and in the "Influence Diagnostics" section. Each statistic is computed for each observation.
Table 55.6: Formulas and Definitions for Diagnostic Statistics
Formula | |
PRED () | Xib |
RES (ri) | |
H (hi) | xi(X'X)-xi' |
STDP | |
STDI | |
STDR | |
LCL | STDP |
LCLM | STDI |
UCL | STDP |
UCLM | STDI |
STUDENT | [(ri)/( STDRi)] |
RSTUDENT | |
COOKD | [1/p] STUDENT2([ STDP/( STDR2)]) |
COVRATIO | |
DFFITS | |
DFBETASj | |
PRESS(predri) | [(ri)/(1-hi)] |
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