Nothing
# these functions originally by Jarrett Byrnes
# methods to generate
# various information criteria from
# sem or adjchisq objects
# as well as generate and AIC table
# last modified 2012-10-02 by J. Fox
logLik.objectiveML <- function(object, ...){
-0.5*deviance(object)
}
# generics
AICc <- function(object, ...) UseMethod("AICc")
CAIC <- function(object, ...) UseMethod ("CAIC")
# methods for sem objects
AIC.objectiveML <- function(object, ..., k) {
deviance(object) + 2*object$t
}
# small sample second order corrected aic
AICc.objectiveML <- function(object, ...) {
deviance(object) + 2*object$t*(object$t + 1)/(object$N - object$t - 1)
}
# Consistent Akaike Information Criterion
CAIC.objectiveML <- function(object, ...) {
props <- semProps(object)
props$chisq - props$df*(1 + log(object$N))
}
BIC.objectiveML <- function(object, ...) {
n <- object$n
n.fix <- object$n.fix
N <- object$N
t <- object$t
df <- n*(n + 1)/2 - t - n.fix*(n.fix + 1)/2
# deviance(object) + object$t*log(object$N)
deviance(object) - df*log(N)
}
# the following are not exported and are just place-keepers for the summary method
BIC.objectiveGLS <- function(object, ...) NULL
AIC.objectiveGLS <- function(object, ...) NULL
AICc.objectiveGLS <- function(object, ...) NULL
CAIC.objectiveGLS <- function(object, ...) NULL
# weights
aicW <- function(a.list, func=AICc){
aiclist <- sapply(a.list, function(x) eval(func(x)), simplify=TRUE)
delta.i <- aiclist - min(aiclist)
aicw <- exp(-0.5*delta.i)/sum(exp(-0.5*delta.i))
return.matrix <- matrix(c(aiclist,delta.i, aicw), ncol=3)
colnames(return.matrix) <- c("IC", "delta.i", "weight")
rownames(return.matrix) <- 1:length(return.matrix[,1])
return(return.matrix)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.