similar to: mlogit package inquiry

Dear R users, When running the program below I receive the following error message: fit <- optim(parm, objective, yt = tyield, hessian = TRUE) Error in as.vector(data) : no method for coercing this S4 class to a vector I can't figure out what the problem is exactly. I imagine that it has something to do with "tyield" being a matrix. Any help on explaining what's going on

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

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Hi: When I call str() on an mlogit object, I seem to get warnings. This code is from an example provided in the mlogit documentation: library(mlogit) data("Train", package="mlogit") tr<-mlogit.data(Train, shape="wide", choice="choice", varying=4:11, sep="", alt.levels=c(1,2), id="id")

I discovered recently that the phrase "Oja median" produces no hits in Jonathan Baron's very valuable R search engine. I found this surprising since I've long regarded this idea as one of the more interesting notions in the multivariate robustness literature. To begin to remedy this oversight I wrote a bivariate version and then decided that writing a general p-variate version

> It might clarify your thinking to note that a seasonal ARIMA model > is just an ``ordinary'' ARIMA model with some coefficients > constrained to be 0 in an efficient way. E.g. a seasonal AR(1) s = > 4 model is the same as an ordinary (nonseasonal) AR(4) model with > coefficients theta_1, theta_2, and theta_3 constrained to be 0. You > can get the same answer as from

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 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: 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

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 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

To back up Ber's please have a look at http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example and/or http://adv-r.had.co.nz/Reproducibility.html John Kane Kingston ON Canada > -----Original Message----- > From: jose.ferraro at logiteng.com > Sent: Wed, 13 Apr 2016 17:18:35 +0000 > To: cdesjard at umn.edu > Subject: Re: [R] reduced set of

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,

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

Hello, I can't figure out why using and not using weights in mlogit yields identical results. My motivation is for the case when an "observation" or "individual" represents a number of individuals. For example, library(mlogit) library(AER) data("TravelMode", package = "AER") TM <- mlogit.data(TravelMode, choice = "choice", shape =

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

Hello, There's a typo in your call to mlogit.data, it should be alt.var="nbChev", not alt.var="noChev". Then the error is different. You should check the call arguments to see if they make sense. Hope this helps, Rui Barradas Em 28-07-2017 13:14, sandoz at free.fr escreveu: > I re post my question with the csv problem fixed. > > Can someone explain the

I am using the mlogit packages and get a data problem, for which I can't find any clue from R archive. code below shows my related code all the way to the error #--------------------------------------------------------------------------- mydata <- data.frame(dependent,x,y,z) mydata$dependent<-as.factor(mydata$dependent) mldata<-mlogit.data(mydata, varying=NULL,

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

Hello, I am using the mlogit package to model diplomatic representation and stability. Here is our sample model - m2 = mlogit(y ~ 0|(time.curr + period), data=dip, alt.levels=c("asym","end","sym","x"), shape="wide", subset=which(mlogdata$curr=="sym")) >From here, we would need to find the probabilities and the standard error of