Average prediction mean squared error.

## 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.

## Examples

```
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_hsp(model)
#> [1] 0.2644378
```