I'm not at all familiar with mlogit or Biogene so I can't really give a definitive answer, but it seems that this would be a very dangerous thing to try.
Looking at the mlogit manual, I see that, like most model objects in R, mlogit has a variety of elements including many of those you specifically seem to be avoiding: data, likelihood functions, etc. You could perhaps make a trivial mlogit object and directly modify the elements you mention, but then you'd want to check each of the functions you run on your object to make sure they don't access the unmodified list elements. A fair compromise is probably to run mlogit on a small sample of your data (I suppose you are using this Biogene program for speed reasons?) to create a "best-approximation object" and then modify directly; that will at least reduce the chance of something too bad happening. I suppose this could be automated to save you a little trouble (just create your own class whose methods consist of getting the mlogit methods, deparsing them and making sure they don't look at an unmodified element, and then passing to the mlogit method) but the smarter path is probably to extract the code from those functions you want to use for prediction and tweak them to use the object you read in directly. Someone may have already implemented a work around though if this is a common problem. Best of luck, Michael On Mon, Oct 17, 2011 at 12:01 PM, Bhargava Sana <bhargava.s...@rsginc.com> wrote: > Michael, > > Thanks for the quick response. I currently have a few models that have been > estimated using Biogeme. I have attached a sample output file from the > estimation. > > I am more concerned about creating a model object from scratch rather than > the reading part. Let us just say if we have a list of variables, > coefficients, and std errors, how can an R model object be created (so that > it can be used for prediction on an R data frame)? I read in the mlogit > documentation that a model is created using an estimation dataset and > formula. I was wondering if there have been previous attempts to setup a > model object without estimating it in R just based on some character > variables. > > Bhargava > > -----Original Message----- > From: R. Michael Weylandt [mailto:michael.weyla...@gmail.com] > Sent: Monday, October 17, 2011 11:44 AM > To: Bhargava Sana > Cc: r-help@r-project.org > Subject: Re: [R] Creation of mlogit models from text file > > You're going to have to say more about your text file if you want > meaningful help: specifically, what is in the file: data, output from > other software, etc? > > There are probably two questions to deal with here: reading in > whatever is in the text file and mapping it to the correct R object > and setting up the mlogit model. For the reading part, try > read.table() or readLines depending on the formatting. For the mlogit, > look at the mlogit package available on CRAN. > > Michael > > On Mon, Oct 17, 2011 at 10:52 AM, Bhargava Sana > <bhargava.s...@rsginc.com> wrote: >> Hello all, >> >> Has anyone tried to create an R mlogit model object from a text file? If >> yes, what would be the best way to do it? I already have models that have >> been estimated using other software and would like to use R to help me make >> predictions for new data. >> >> Thank you! >> >> Bhargava Sana >> >> >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
