Description Usage Arguments Details Value References See Also Examples
Estimated error of prediction, assuming multivariate normality.
1 | ols_msep(model)
|
model |
An object of class |
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
Estimated error of prediction of the model.
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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