ols_hsp {olsrr} | R Documentation |
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.
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)
ols_hsp(model)