On Tue, 26 Oct 2010, Marc Schwartz wrote:
On Oct 26, 2010, at 2:59 PM, Ben Hunter wrote:
Hi everyone,
Why am I having such a tough time finding a way to put an mlogit summary
table into latex? Everywhere I read says that using Sweave and latex is the
most sophisticated, dynamic way to get output, but it appears very limited
in this respect. I'm just starting out with Sweave and LaTeX and I've only
been working with R for about 5 months. I'm suspecting this is something
that just hasn't been done yet, but certainly there is a workaround I don't
know about. Hope so, anyway.
Thanks a lot.
Ben
Ben,
One thing to keep in mind is that the LaTeX related functions (save Sweave itself) are
contributed by folks via third party packages. They are not part of the "core"
R offering.
The two primary packages that offer LaTeX related output for common R objects
are xtable and Hmisc (via the latex() function). In both cases, the object
class methods that are included likely reflect, to a large extent, the most
commonly used R objects by the authors who are then motivated to write the
functions. In turn, these also tend to represent common usage more generally.
There may very well be someone out there who has created a specific function to
generate LaTeX output for the two functions of interest here, but they may not
have made them generally available for various reasons.
That being said, if you can take the relevant content of the R objects
generated by mlogit and/or multinom and construct a matrix or data frame from
them, you can then use the xtable() methods for a matrix or data frame to
generate formatted LaTeX output in your Sweave document. Since most relevant
LaTeX output is tabular in nature, using either a matrix or data frame is a
general purpose approach to getting the content you may desire, in lieu of
having a method specifically for a particular R object.
Some months back I discussed with the "xtable" folks the possibility of
including some default method leveraging the coefplot() function from the
"lmtest" package which computes the usual table of coefficients/standard
errors/test statistics/p-values. A quick and dirty hack would be the
following:
## load "xtable" and provide a new xtable() method for
## "coeftest" objects
library("xtable")
xtable.coeftest <- function(x, ...) {
xtable:::xtable.summary.lm(list(coef = unclass(x)), ...)
}
With that you can do xtable(coeftest(fitted_object)) for a rather wide
class of models. See below for worked examples of mlogit() and multinom().
hth,
Z
## mlogit() model from "mlogit" package
library("mlogit")
data("Fishing", package = "mlogit")
Fish <- mlogit.data(Fishing, varying = c(2:9),
shape = "wide", choice = "mode")
fm_mlogit <- mlogit(mode ~ 0 | income, data = Fish)
## load "lmtest" to compute coeftest()
library("lmtest")
coeftest(fm_mlogit)
## export via xtable()
xtable(coeftest(fm_mlogit))
## multinom() model from "nnet" package
library("nnet")
fm_multinom <- multinom(mode ~ income, data = Fishing)
## the coeftest() method is in "AER" package
library("AER")
coeftest(fm_multinom)
xtable(coeftest(fm_multinom))
In addition, while this may not be a direction you wish to take, I did locate
an Export plug in for the Rcmdr package that appears to have some relevant
functionality for the summary.multinom() class. You may wish to consider that
approach. More information is at:
http://cran.r-project.org/web/packages/RcmdrPlugin.Export/
HTH,
Marc Schwartz
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