similar to: Mlogit missing value problem

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

Hi I have estimated parameters of my data with mlogit and the following commands. I would like to know also the McFadden R^2 and the intercept, could soweone tell me how that can be done? library(RODBC) library(mlogit) library(foreign) z<-odbcConnectExcel("D:\\MALLI11ARVOT.xls") y<-sqlFetch(z,"Taul1")

Hi, I am trying to use mlogit in R to analyse a block design choice experiment dataset. The 12 choice sets/cards have been randomly assigned to 3 different blocks and each respondent answers all sets from one block (i.e. each respondent chooses from 4 choice sets). In total I have 2336 rows of data from 292 respondents. The data looks like this (2 of the three blocks): ID Sex Age Block Card

Hallo together, I am trying to use the nmkb() optimizer and I have problems using the function, as it causes the following error message Fehler (error)* in while (nf < maxfeval & restarts < restarts.max & dist > ftol & : Fehlender Wert (missing value)* , wo (where)* TRUE/FALSE n?tig ist (is required)* *translation Do I need to adjust the control ?

Here's a quick patch to have either horz or vert (instead of both) maximized windows honor the "ignore" option: --- src/window.c +++ src/window.c @@ -4012,7 +4012,7 @@ constrainNewWindowSize (CompWindow *w, if (d->opt[COMP_DISPLAY_OPTION_IGNORE_HINTS_WHEN_MAXIMIZED].value.b) { - if ((w->state & MAXIMIZE_STATE) == MAXIMIZE_STATE) + if (w->state

Dear all, I am using the nlsLM function to fit a Lorentzian function to my experimental data. The LM algorithm should allow to specify limits, but the upper limit appears not to work as expected in my code. The parameter 'w', which is peak width at half maximuim always hits the upper limit if the limit is specified. I would expect the value to be in-between the upper and lower limit with

Hi I have an example file in excel and i have following instructions to open and analyze the data in it. > library(RODBC) > library(mlogit) > z<-odbcConnectExcel("C:\\2008 Racedata.xls") Everything ok untill the next command > x<-mlogit.data(y,choice="winner",shape="long",id.var="datekey",alt.var="horseno") Error in

hi, I have been trying to do this in R (have implemented it in Excel) but I have been using a very inefficent way (loops etc.). I have matrix A (columns are years and ages are rows) and matrix B (columns are birth yrs and rows are ages) I would like to first turn matrix A into matrix B And then I would like to convert matrix B back again to the original matrix A. (I have left out details of

How can I right justify the right-axis tick values? They appear in the example below as left-justified. I have tried several different ways and all fail in different ways. The example below creates the right axis tick value with no attempt at adjustment. alternates I have tried are 1. formatting the values. This doesn't work because they are in a proportional font and the blanks are too

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")

I've been working on a multinomial logit model, trying to predict vegetation types as a function of total phosphorus. Previous responses to my postings have pointed me to the mlogit package. I'm now trying to work examples and my data using this package. data("Fishing", package = "mlogit") Fish <- mlogit.data(Fishing, varying = c(4:11), shape = "wide",

I'm trying to fit a multinominal logistic model using package mlogit. I have 15 independent variables. The code looks like this: m<-mlogit(score~0|f1+f2+f3+f4+f5+f6+f7+f8+f9+f10+f11+f12+f13+f14+f15, data, reflevel="1") And it gives the following error message: Error in parse(text = x) : unexpected ')' in "score ~ 0 + alt:(f1 + f2 + f3 + f4 + f5 + f6 + f7 + f8 + f9

I am new to R but I have managed to use mlogit to run multivariate logit models successfully. My data violates the Independence of Irrelevant Alternatives assumption and now I would like to run a mixed logit model. It is a "wide" data set with 9 independent (individual) variables and three choices (variable Y). The database is in a cvs file called CAU. This is the code I have run

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

Hello, I'm trying to run a mlogit regression on my data, and have been unsuccessful so far. The data I am working with consist of many observations of how people react when given a certain number. I have just 2 data points per observation: a number (there are ~300 different possible numbers) and then a reaction (either 0, 1, or 2). The reactions are mutually exclusive and exhaustive. I am

Dear all, I am trying to run a mixed multinomial logit model in R since my response variable has 4 non-ordinal categories. I am using the package mlogit that estimates the parameters by maximum likelihood methods. First of all, I prepared my data using the mlogit.data command. In the mlogit command, one can introduce alternative-specific (fixed factors??) and individual-specific (random

Hi, I'm trying to fit a multinomial logistic regression to my data which consists of 5 discrete variables (scales 1:10) and 1000 observations. I get the following error: Error in `row.names<-.data.frame`(`*tmp*`, value = c("NA.NA", "NA.NA", : duplicate 'row.names' are not allowed In addition: Warning message: non-unique value when setting

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) >

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]]

Dear all, ? I am implementing a stochastic utility model that will eventually make use of multinomial logit. I found that there is a package in R called mlogit. I am not sure whether I have already found the correct package or software. May I ask am I correct? ? Basically, let's say ? I have observations of n outcomes, for each outcome 1<=i<=n, they were selected by a choice from a set