Average prediction mean squared error.

ols_hsp(model)

## Arguments

model An object of class lm.

## Value

Hocking's Sp of the model.

## Details

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

## References

Hocking, R. R. (1976). “The Analysis and Selection of Variables in a Linear Regression.” Biometrics 32:1–50.

Other model selection criteria: ols_aic, ols_apc, ols_fpe, ols_mallows_cp, ols_msep, ols_sbc, ols_sbic
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)