Hocking's Sp
Average prediction mean squared error.
ols_hsp(model)
model |
An object of class |
Hocking's Sp criterion is an adjustment of the residual sum of Squares. Minimize this criterion.
MSE / (n - p - 1)
where MSE = SSE / (n - p), n is the sample size and p is the number of predictors including the intercept
Hocking's Sp of the model.
Hocking, R. R. (1976). “The Analysis and Selection of Variables in a Linear Regression.” Biometrics 32:1–50.
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars) ols_hsp(model)
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