similar to: mlogit and weights

I am trying to estimate multinomial logit models off of a .csv table in IDCASE IDALT format where I have ROWS HHID PERID CASE ALTNUM NUMALTS CHOSEN IVTT OVTT TVTT COST DIST WKZONE HMZONE RSPOPDEN RSEMPDEN WKPOPDEN.... 1 1 2 1 1 1 5 1 13.38 2.00 15.38 70.63 7.69 664 726 15.52 9.96 37.26 2 2 2 1 1 2 5 0 18.38 2.00

Philipp Benner reported a Debian bug report against r-cran-rpart aka rpart. In short, the issue has to do with how rpart evaluates a formula and supporting arguments, in particular 'weights'. A simple contrived example is ----------------------------------------------------------------------------- library(rpart) ## using data from help(rpart), set up simple example myformula <-

Hello, guys. Q1. now I have load all the docid and its document data into a dictionary for faster loading data instead of calling Xapian::MSetIterator i; i.get_document().get_data(); but I was happened to discover that the dictionaries got by such two method were different: both methods use DB1, DB2 method 1: Xapian::Database db = Xapian::Database(the path of DB1); Xapian::Database db2 =

Hello! I wrote a code that works, but it looks ugly to me - it's full of loops. I am sure there is a much more elegant and shorter way to do it. Thanks a lot for any hints! Dimitri # I have a data frame: x<-data.frame(group=c("group1","group2","group1","group2"), myweight=c(0.4,0.6,0.4,0.6),

Hi, I have a number of spatial weight files and using Roger Bivand's spdep, I would like to 1. Convert them into neighbor lists using 2. Convert the neighbor lists into spatial weights For a given file, the syntax would be mygal_nb1 <- read.gal("mygalfile1", override.id = TRUE) myweight1 <- nb2listw(mygal_nb1) I have mygalfile[i] with i from 1 through to 6 and would like to

Hi, While searching for a project which matches my interest andskill level, I found this project named Matcher Optimization. This project is really challenging and excting from my view point and I would like to be a part of this project. Optimization techniques metioned in the reference links provided will take some time for me to have a good understanding about them. But I am trying to get my

Hello, I've been getting the following error when using the mlogit function from the mlogit package This is one of the examples provided in the Package "mlogit" January 27, 2010 description data("Fishing", package="mlogit") Fish <- mlogit.data(Fishing, varying = c(4:11), shape="wide", choice="mode") summary(mlogit(mode ~ pr + ca - 1,

Hi all, I have been working through the examples in one of the vignettes associated with the 'mlogit' package, 'Kenneth Train's exercises using the mlogit package for R.' In spite of using the code unchanged, as well as the data used in the examples, I have been unable to run a Wald test to test two models. Specifically, I have run the following command, where mc and mi2 are

I am trying to follow this example for multinomial logistic regression http://www.ats.ucla.edu/stat/r/dae/mlogit.htm However, I cannot get it to work properly. This is the output I get, and I get an error when I try to use the mlogit function. Any ideas as to why this happens? > mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/mlogit.csv")) > attach(mydata) >

I am learning five mlogits as follows v1.model<-mlogit(v1~1|v2+v3+v4+v5, data=mlogit.v1.data, reflevel="1") v2.model<-mlogit(v2~1|v1+v3+v4+v5, data=mlogit.v2.data, reflevel="1") v3.model<-mlogit(v3~1|v1+v2+v4+v5, data=mlogit.v3.data, reflevel="1") v4.model<-mlogit(v4~1|v1+v2+v3+v5, data=mlogit.v4.data, reflevel="1")

Hello: Has anyone tried to model-based recursive partition (using mob from package party; thanks Achim and colleagues) a data set based on a multinomial logit model (using mlogit from package mlogit; thanks Yves)? I attempted to do so, but there are at least two reasons why I could not. First, in mob I am not quite sure that a model of class StatModel exists for mlogit models. Second, as

Sir, I want to fit a multinomial logistic regression in R.I think mlogit() is the function for doing this. mlogit () is in packege globaltest.But, I can not install this package. I use the following: install.packages("globaltest") Can you help me? Regards, Suman Dhara [[alternative HTML version deleted]]

Hi all - my first time here and am having an issue with the Predict function. I am using a tutorial as a guide, locate here: http://www.ats.ucla.edu/STAT/R/dae/mlogit.htm My code gives this error > newdata1$predicted <- predict(mlogit,newdata=newdata1,type="response") Error in `$<-.data.frame`(`*tmp*`, "predicted", value = c(0.332822934960197, : replacement has

Hi Jose, You're referring to your response variable when you're saying it's missing some of the choices, right? Are your response choices ever known or do they just occur with extremely low frequency? Either way, I think the mlogit package would be inappropriate for you. I imagine you would have much better luck using MCMCpack or writing a model with rstan or something Bayesian.

Hi All, I am attempting to build a Multinomial Logit model with dummy variables of the following form: Dependent Variable : 0-8 Discrete Choices Dummy Variable 1: 965 dummy varsghpow at student.monash.edu.augh@gp1.com Dummy Variable 2: 805 dummy vars The data set I am using has the dummy columns pre-created, so it's a table of 72,381 rows and 1770 columns. The first 965 columns represent

Hi I am trying to estimate parameter values with mlogit. I attach a part of my data. My code is x=mlogit.data(y,choice="voittaja",shape="long",id.var="id",alt.var="numero") summary(mlogit(voittaja ~ Ie-1 , data=x, na.action=na.pass)) But i get Error in if (abs(x - oldx) < ftol) { : missing value where TRUE/FALSE needed Because there is Na

code? example data? We can only guess based on your vague post. "PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code." Moreover, this sounds like a statistical question, not a question about R programming, and so might be more appropriate for a statistical list like stats.stackexchange.com .

Hello,  I am pretty new to mlogit, and still trying to figure out what models to use.I have a data set of N individuals, each of which faces I alternatives. The utility function of individual n, for choice i is:  u(i,n) = alpha(i) * x1(i,n) + beta * x2(i,n)  where alpha(i) is the individual specific parameter, and beta is shared among all individuals. I don't really know how to set this up

Hi, Please help about the error I am getting after the h1.dat<- line : this line worked with much more independant variables and bigger data. This time I want to work with just 2 variables cteD & cteTh. What is wrong ? > setwd("C:/Rstudio/Trot") > library(mlogit) > horse1.data<-read.csv("cte2.csv") >

I am trying to perform a backwards stepwise variable selection with an mlogit model. The usual functions, step(), drop1(), and dropterm() do not work for mlogit models. Update() works but I am only able to use it manually, i.e. I have to type in each variable I wish to remove by hand on a separate line. My goal is to write some code that will systematically remove a certain set of variables