similar to: Multinomial Logit and p-values

Hi, Is there a way to use regular expressions to capture two or more words in a sentence? For example, I wish to to find all the lines that have the words "thomas", "perl", and "program", such as "thomas uses a program called perl", or "perl is a program that thomas uses", etc. I'm sure this is a very easy task, I would greatly appreciate

Dear R-Help, I'm hoping to find a Multinomial Nested Logit package in R. It would be great to find something analogous to "PROC MDC" in SAS: > The MDC (Multinomial Discrete Choice) procedure analyzes models > where the > choice set consists of multiple alternatives. This procedure > supports conditional logit, > mixed logit, heteroscedastic extreme value,

Hi everyone? Does anybody know how can I estimate a Latent class multinomial (or conditional) logit using R? I have tried flexmix, poLCA, and they do not seem to support this model. thanks in advance adan -- View this message in context: http://r.789695.n4.nabble.com/Latent-class-multinomial-or-conditional-logit-using-R-tp4230083p4230083.html Sent from the R help mailing list archive at

Good morning, I'd like to estimate a simple multinomial logit model in R (not a McFadden conditional logit). For instance, I'd like to estimate the probability of someone having one of eight titles in a company with the independent variables being the company characteristics. A binary logit is well documented. What about the multinomial? Thanks, Walt Paczkowski

Hi I am wanting to fit some multinomial logit models (multinom command in package nnet) Is it possible to do any model checking techniques on these models e.g. residual, leverage etc. I cannot seem to find any commands that will allow me to do this. Many thanks ---------------------- L.E.Gross L.E.Gross at maths.hull.ac.uk

I am attempted to examine the temporal independence of my data set and think I need an unordered multinomial logistic regression (or logit model) with repeated measures to do so. The data in question is location of chickens. Chickens could be in any one of 5 locations when a snapshot sample was taken. The locations of chickens (bird) in 8 pens (pen) were scored twice a day (AMPM) for 20 days

Dear all, I am having a hard time attempting to do a multinomial logit modeling in R. I am trying to analyze a dataset whereby there are 3 scenarios with 4 difference choice parameters. In particular ? I am having a hard time arranging this into a .csv format. What sorts of headings should I put in the column headers to reflect the variables and parameters for the total number of choice made

Dear R users, I would like to know if there is a package in R that estimates multinomial logit models (without using surrogate Poisson models) -or even better- nested multinomial logit models? I am using the Windows version of R (Windows 95). To my understanding, the S package called nnet does that, but it seems not to work in R. Thanking in advance for any help, Marjo Pyy-Martikainen

A multinomial logit model can be specified as a conditional logit model after restructuring the data. Doing so gives flexibility in imposing restrictions on the dependent variable. One application is to specify a loglinear model for square tables, e.g. quasi-symmetry or quasi-independence, as a multinomial logit model with covariates. Further details on this technique and examples with several

Hi all, I have a dataset with a response variable with three categories (1, 2, 3) and a lot of continuous variables. I'd like to make a MLR with these variables. I've been watching the libraries nnet and zelig for this purpose but I don't understand them well. I use a training sample data to make the MLR. train.set <- sample(1:1000,1000*0.7) I have done this: library(nnet) net

Dear all, 1)how can I easily get p value for the coefficients of factors in a multinomial model? 2)why the p values for "type III" test with Anova are not identical to that from SAS? for example: A,B and C are categorical variables,but the proportions of each level in each categorical variables are not balance. Y is a nominal variables(>=3 categories); To do

Hello, after calculating a multinomial logit regression on my data, I compared the output to an output retrieved with SPSS 18 (Mac). The coefficients appear to be the same, but the logLik (and therefore fit) values differ widely. Why? The regression in R: set.seed(1234) df <- data.frame( "y"=factor(sample(LETTERS[1:3], 143, repl=T, prob=c(4, 1, 10))), "a"=sample(1:5,

If you're able to reproduce the infinite loop with -O3 then you should be able to dump out the IR that causes `opt -instcombine` to infloop, unless the bug is truly esoteric (e.g. only caused by a specific use-list ordering). Maybe take a closer look at the output from `opt -print-before-all -O3`? Alternatively you can use bugpoint to minimize the IR to get a small reproducer that causes

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

Dear All, Can someone please tell me if there is a provision in R to fit a random coefficient multinomial logistic regression. Thanks in advance for your help and suggestions. Regards Murthy.N.M

Thanks. I could take a look at the lines and all of them have smull instruction like 'smull r0, r1, r0, r1'. Won On Wed, Jul 8, 2009 at 2:54 PM, Dale Johannesen <dalej at apple.com> wrote: > > On Jul 8, 2009, at 12:52 PMPDT, Won J Jeon wrote: > > I tried a couple of options (-mcpu=arm1136j-s, -mcpu=arm1136jf-s, > -march=armv6, ...) to let the compile know the

Please, could you tell me how to enter a mixed or a purely conditional multinomial logit model in NNET. I know how to do a multinomial logit in NNET but I don't know how to do conditional or mixed models using this package. I do know how to do this with VGAM - but would like to compare my results to those obtained by NNET. Thanks. Raffaele.

I'm attempting to creat multinomial logistic regression model using the following code: mlogit<- vglm(ME ~ HIST,family=multinomial(),na.action = na.pass) ME (dependent variable) has three levels (0,1,2) How do I declare a reference outcome (either 0,1,2)?

Hi, I am inexperienced with ML and R so please be tolerant :) I am trying to replicate the method I have seen in a paper without success. If my understanding is correct (a big 'IF') it seems to use Multinomial Logit on multiple groups of various sizes, with 'nature' selecting the choice (the winner) - then uses Maximum Likelihood to optimise the parameters to produce a model for

I am trying to estimate a latent class multinomial logit regression with flexmix. I am not sure if I should do it as follows: m4<-flexmix(cbind(y,1-y)~x1+x2|id,model=FLXMRglm(family="binomial"),data=NPreg,k=2) , where id links each row with the corresponding respondent. Each respondent has 4 alternatives to chose from. y takes the value 1 only for the alternative chosen; x1 and