Estimated error of prediction, assuming multivariate normality.

ols_msep(model)

model | An object of class |
---|

Estimated error of prediction of the model.

Computes the estimated mean square error of prediction assuming that both independent and dependent variables are multivariate normal.

$$MSE(n + 1)(n - 2) / n(n - p - 1)$$

where \(MSE = SSE / (n - p)\), n is the sample size and p is the number of predictors including the intercept

Stein, C. (1960). “Multiple Regression.” In Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling, edited by I. Olkin, S. G. Ghurye, W. Hoeffding, W. G. Madow, and H. B. Mann, 264–305. Stanford, CA: Stanford University Press.

Darlington, R. B. (1968). “Multiple Regression in Psychological Research and Practice.” Psychological Bulletin 69:161–182.

Other model selection criteria:
`ols_aic()`

,
`ols_apc()`

,
`ols_fpe()`

,
`ols_hsp()`

,
`ols_mallows_cp()`

,
`ols_sbc()`

,
`ols_sbic()`

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