Average prediction mean squared error.

ols_hsp(model)

model | An object of class |
---|

Hocking's Sp of the model.

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, 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()`

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