Description Usage Arguments Details Value Author(s) References See Also Examples
Consistent AIC
1 2 3 |
object |
A fitted model object. |
... |
More fitted model objects. |
alpha |
Weight factor between 0 and 1 (see Details). Default value is 0.5. |
CAIC = alpha * AIC + (1 - alpha) * BIC
Atomic vector if only one input object provided,
a data frame similar to what is returned by
AIC
and BIC
if there are more than one input objects.
Subhash Lele and Peter Solymos
Bozdogan, H. 1987. Model selection and Akaike's information criterion (AIC): the general theory and its analytical extensions. Psychometrika, 52, 345-370.
Taper, M. 2004. Model identification from many candidates. In: Taper, M. and Lele, S. R. (eds), The Nature of Scientific Evidence: Statistical, Philosophical, and Empirical Considerations. The University of Chicago Press, Chicago, IL, 567 pp.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## compare some random models
y <- rnorm(10)
a <- lm(y ~ runif(10))
b <- lm(y ~ runif(10))
0.5*(AIC(a) + BIC(a))
CAIC(a)
AIC(a)
CAIC(a, alpha=1)
BIC(a)
CAIC(a, alpha=0)
CAIC(a, b)
CAIC(a, b, alpha=0.2)
## you can use global option
## useful when inside of xv or bootstrap
## no need for extra argument
getOption("CAIC_alpha")
op <- options(CAIC_alpha = 0.2)
getOption("CAIC_alpha")
CAIC(a,b)
options(op)
getOption("CAIC_alpha")
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