olsrr (version 0.5.3)

ols_hsp: Hocking's Sp

Description

Average prediction mean squared error.

Usage

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). <U+201C>The Analysis and Selection of Variables in a Linear Regression.<U+201D> Biometrics 32:1<U+2013>50.

See Also

Other model selection criteria: ols_aic, ols_apc, ols_fpe, ols_mallows_cp, ols_msep, ols_sbc, ols_sbic

Examples

Run this code
# NOT RUN {
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_hsp(model)

# }

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