similar to: fitting multinomial logistic regression

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 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

Sir, I want to calculate double integral in R. Is there any function to do this? Regards, Suman Dhara [[alternative HTML version deleted]]

Sir, I want to store the column name of a data frame as a vector and use the vector to remove a column of the data frame ,if required. Thanks, Suman Dhara [[alternative HTML version deleted]]

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 I am trying to fit a multinomial logistic regression to a data set with a size of 94279 by 14 entries. The data frame has one "sample" column which is the categorical variable, and the number of different categories is 9. The size of the data set (as a csv file) is less than 10 MB. I tried to fit a multinomial logistic regression, either using vglm() from the VGAM package or

Sir, I have a problem regarding partitioning a matrix.I state my problem as follows: I have a y vector of length say 1000.Variable y has 4 levels say 0,1,2.Corresponding to each y(response), I have a x-vector(explanatory) as a row of X matrix.Now, I want to partition the X matrix into 3 submatrices say x1,x2,x3 corresponding to each level of y.Is there any function to do this in R or how can I

Sir, I want to export the results of R in a data frame. So I want to give rownames,columnnames & title to the data-frame.I have applied the following: data.frame(matrix(c(...),nrow=,ncol=),row.names=c("a","b"),col.names=c("c","d"),title="aaa") But, it does not work. Can you help me? Regards, Suman Dhara [[alternative HTML version

Sir, I am working with multiclass discriminant analysis.(say response variable has 3classes).In R, using lda(), I get 2 sets of coefficients for the discriminant function.Now, I want to put a new x-vector(vector of independent variables) and want to check it corresponds to which class of y.Is there any formula for doing this? or how can I do this? Regards, Suman Dhara [[alternative HTML

Sir, I want to draw random from any multivariate disrtibution. Is there any function in R to do this? Regards, Suman Dhara [[alternative HTML version deleted]]

Dear Colleagues I have been fitting some multinomial logistic regression models using R (version 1.6.1 on a linux box) and Stata 7. Although the vast majority of the parameter estimates and standard errors I get from R are the same as those from Stata (given rounding errors and so on), there are a few estimates for the same model which are quite different. I would be most grateful if

Sir, I am working on fitting distribution on multivariate financial data and then simulate observations from that fitted distribution. I use stepAIC.ghyp() function of 'ghyp' library which select the best fitted distribution from generalized hyperbolic distribution class on the given dataset. data(indices) # Multivariate case: aic.mv <- stepAIC.ghyp(indices, dist =

Dear R-group, Could somebody recommend a package that can deal with a multinomial response variable (choice of breeding tactic in mice, which has four unordered levels), multiply-imputed data (generated using the Amelia package) and two non-nested random effects: individual identity (133 individuals made up to four choices each) and year (for which there are six levels and sample size varies

Hello dear R-users, does any of you know a way to perform a multinomial regression with clustered data (i.e. repeated measurements)? I made the first analysis with Stata option vce cluster in the mlogit command but was looking for a similar functionality in R too... thanks all! niccolò [[alternative HTML version deleted]]

I want to analyse data with an unordered, multi-level outcome variable, y. I am asking for the appropriate method (or R procedure) to use for this analysis. > N <- 500 > set.seed(1234) > data0 <- data.frame(y = as.factor(sample(LETTERS[1:3], N, repl = T, + prob = c(10, 12, 14))), x1 = sample(1:7, N, repl = T, prob = c(8, + 8, 9, 15, 9, 9, 8)), x2 = sample(1:7, N, repl =

I want to get the logLik to calculate McFadden.R2 ,ML.R2 and Cragg.Uhler.R2, but the value from multinom does not have logLik.So my quetion is : is logLik meaningful to multinomial logistic model from multinom?If it does, how can I get it? Thank you! ps: I konw VGAM has function to get the multinomial logistic model with logLik, but I prefer use the function from "official" R

Hi, I would like to apply the L-BFGS optimization algorithm to compute the MLE of a multilevel multinomial Logistic Regression. The likelihood formula for this model has as one of the summands the formula for computing the likelihood of an ordinary (single-level) multinomial logit regression. So I would basically need the R implementation for this formula. The L-BFGS algorithm also requires

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

On May 24, 2011; 11:06pm Belle wrote: > Does anyone know how to run Multinomial logistical Model in R in order to > get predicted probability? Yes. I could stop there but you shouldn't. The author of the package provides plenty of examples (and two good vignettes) showing you how to do this. Suggest you do some work in that area. Look especially at how model formulas 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) >