Please note, I told you that the deviance was minus twice log-likelihood
unless summ > 0. I had not checked the latter case, where it is not
obvious, but I did not say it was invalid.
In fact the answer is to be found on p.203 of MASS4 (we do ask people to
read the supporting documentation), and this is valid also for summ > 0.
I will add a comment to the help file.
On Wed, 22 Feb 2006, ronggui wrote:
Here is a function for calculating the measures of fit for
multinomial logistic model (using nnet::multinom).If anything wrong ,I
hope experts point it out.Thank you.
fitstat <- function(object) {
#thanks Ripley, B. D. for telling how to get the LogLik and when is invalid.
{if (!is.null(object$call$summ) && !identical(object$call$summ,0))
stop("when 'summ' argument is not zero,can NOT get Loglik") }
object.base <- update(object,.~1,trace=FALSE)
dev.base <- deviance(object.base) ; L.base <- - dev.base/2
dev.full <- deviance(object) ; L.full <- - dev.full/2
G2 <- dev.base - dev.full
df <- object$edf - object.base$edf
LR.test.p <- pchisq(G2,df,lower=F)
aic <- object$AIC
n<-dim(object$residuals)[1]
#get the predict value to cal count R2
pre <- predict(object,type="class")
y <- eval.parent(object$call$data)[,as.character(object$call$formula[[2]])]
if (!identical(length(y),length(pre))) stop("Length not matched.")
tab <- table(y,pre)
if (!identical(dim(tab)[1],dim(tab)[2])) stop("pred and y have diff nlevels")
ad <- max(rowSums(tab))#max of row sum
#cal R2
ML.R2 <- 1-exp(-G2/n)
McFadden.R2 <- 1-(L.full/L.base)
McFadden.Adj.R2 <- 1-((L.full-mod$edf)/L.base)
Cragg.Uhler.R2 <- ML.R2/(1-exp(2*L.base/n))
Count.R2 <- sum(diag(tab))/sum(tab)
Count.adj.R2 <- (sum(diag(tab))-ad)/(sum(tab)-ad)
#get the result
res<-list(LR=G2,df=df,LR.test.p =LR.test.p
,aic=aic,ML.R2=ML.R2,Cragg.Uhler.R2=Cragg.Uhler.R2,McFadden.R2
=McFadden.R2
,McFadden.Adj.R2=McFadden.Adj.R2,Count.R2=Count.R2,Count.adj.R2=Count.adj.R2)
#print the result
cat("\n",
paste(rep("-",21)),
"\n The Fitstats are : \n",
sprintf("G2(%d) = %f",df,G2),
" ,Prob ",format.pval(LR.test.p),
"\n",sprintf("AIC = %f",aic),
sprintf(",ML.R2 = %f \n",ML.R2),
paste(rep("-",21)),"\n",
sprintf("Cragg.Uhler.R2 = %f \n",Cragg.Uhler.R2),
sprintf("McFadden.R2 = %f \n",McFadden.R2),
sprintf("McFadden.Adj.R2 = %f \n",McFadden.Adj.R2),
sprintf("Count.R2 = %f \n",Count.R2),
sprintf("Count.adj.R2 = %f \n",Count.adj.R2),
"\n Note:The maxinum of ML R2 is less than 1 \n",
paste(rep("-",21)),"\n")
invisible(res)
}
#example
require(nnet)
data(mexico,package="Zelig")
mod <- multinom(vote88 ~ pristr + othcok + othsocok,mexico)
summary(mod,cor=F)
fitstat(mod)
#reference:
#J. SCOTT LONG and JEREMY FREESE,REGRESSION MODELS FOR CATEGORICAL
DEPENDENT VARIABLES USING STATA.
fitstat(mod)
- - - - - - - - - - - - - - - - - - - - -
The Fitstats are :
G2(6) = 381.351620 ,Prob < 2.22e-16
AIC = 2376.571142 ,ML.R2 = 0.244679
- - - - - - - - - - - - - - - - - - - - -
Cragg.Uhler.R2 = 0.282204
McFadden.R2 = 0.139082
McFadden.Adj.R2 = 0.133247
Count.R2 = 0.596026
Count.adj.R2 = 0.123003
Note:The maxinum of ML R2 is less than 1
- - - - - - - - - - - - - - - - - - - - -
ÔÚ 06-2-22£¬ronggui<[EMAIL PROTECTED]> дµÀ£º
So it's valid to get logLik (deviance/-2) when the summ argument is unused?
Thank you.
2006/2/22, Prof Brian Ripley <[EMAIL PROTECTED]>:
On Wed, 22 Feb 2006, ronggui wrote:
I want to get the logLik to calculate McFadden.R2 ,ML.R2 and
Cragg.Uhler.R2, but the value from multinom does not have logLik.So my
quetion is : is logLik meaningful to multinomial logistic model from
multinom?If it does, how can I get it?
From the help page:
Value:
A 'nnet' object with additional components:
deviance: the residual deviance.
So it has a residual deviance. That is -2 log Lik in many cases (but not
if the argument 'summ' is used)
Thank you!
ps: I konw VGAM has function to get the multinomial logistic model
with logLik, but I prefer use the function from "official" R
packages .
--
ronggui
Deparment of Sociology
Fudan University
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
--
»ÆÈÙ¹ó
Deparment of Sociology
Fudan University
--
ronggui
Deparment of Sociology
Fudan University
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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