ols_press {olsrr} | R Documentation |
PRESS
Description
PRESS (prediction sum of squares) tells you how well the model will predict new data.
Usage
ols_press(model)
Arguments
model |
An object of class |
Details
The prediction sum of squares (PRESS) is the sum of squares of the prediction error. Each fitted to obtain the predicted value for the ith observation. Use PRESS to assess your model's predictive ability. Usually, the smaller the PRESS value, the better the model's predictive ability.
Value
Predicted sum of squares of the model.
References
Kutner, MH, Nachtscheim CJ, Neter J and Li W., 2004, Applied Linear Statistical Models (5th edition). Chicago, IL., McGraw Hill/Irwin.
See Also
Other influence measures:
ols_hadi()
,
ols_leverage()
,
ols_pred_rsq()
Examples
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_press(model)
[Package olsrr version 0.6.0 Index]