umxWeightedAIC: AIC weight-based conditional probabilities.

umxWeightedAICR Documentation

AIC weight-based conditional probabilities.

Description

Returns the best model by AIC, and computes the probabilities according to AIC weight-based conditional probabilities (Wagenmakers & Farrell, 2004).

Usage

umxWeightedAIC(models, digits = 2)

Arguments

models

a list of models to compare.

digits

(default 2)

Value

  • Best model

References

See Also

  • AIC()

Other Miscellaneous Stats Functions: FishersMethod(), SE_from_p(), geometric_mean(), harmonic_mean(), oddsratio(), reliability(), umxCov2cor(), umxHetCor(), umxParan(), umx_apply(), umx_cor(), umx_means(), umx_r_test(), umx_round(), umx_scale(), umx_var(), umx

Examples

l1 = lm(mpg~ wt + disp, data=mtcars)
l2 = lm(mpg~ wt, data=mtcars)
umxWeightedAIC(models = list(l1, l2))

umx documentation built on May 29, 2024, 5:40 a.m.