[R] does multinomial logistic model from multinom (nnet) has logLik?

[ronggui]

I should ues "Not obvious " instead of "invalid", this is my mistake.

2006/2/24, Prof Brian Ripley <ripley at stats.ox.ac.uk>:
> 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 did read the help page in nnet.And MASS4 is not avaivable  just now :(

I will check that when I can.

> I will add a comment to the help file.

appreciate!


> 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 not obvious.
> > {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
> > - - - - - - - - - - - - - - - - - - - - -
> >
> > ÔÚ 06-2-22£¬ronggui<ronggui.huang at gmail.com> Ð´µÀ£º
> >> So it's valid to get logLik (deviance/-2) when the summ argument is unused?
> >>
> >> Thank you.
> >>
> >> 2006/2/22, Prof Brian Ripley <ripley at stats.ox.ac.uk>:
> >>> 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,                  ripley at stats.ox.ac.uk
> >>> 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
> >>>
> >>
> >>
> >> --
> >> »ÆÈÙ¹ó
> >> Deparment of Sociology
> >> Fudan University
> >>
> >
> >
> > --
> > ronggui
> > Deparment of Sociology
> > Fudan University
> >
> >
>
> --
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> 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
>


--
»ÆÈÙ¹ó
Deparment of Sociology
Fudan University