similar to: multinomial probit

Hi all, Does anybody have a hint on what may be going wrong in this R code? I mimic the sample code from the MNP developers but I seem unable to get the choice specific variables right. Thanks, Joan Serra > rm(list=ls()) > library(foreign) > small<-read.spss("small.sav") Warning message: small.sav: Unrecognized record type 7, subtype 13 encountered in system file. >

Hi, I recently found the MNP package. Out of curiosity, I tried to reproduce results from Greene (Econometric Analysis, fourth edition) on page 874. The signs of the estimates are all opposite those of Greene's table. Might anyone be able to tell me what I am doing wrong? I have attached the function call, the coefficients, and a few rows of the data. The dataset has 210 observations.

Hi, I'm writing an R package using the C code i've written. I'm wondering if anyone knows an easy way to calculate an inverse and cholesky factor of a matrix using the Fortran/C library of R: and how to call them from C. My code is based on the Numerical Reciepe code, and I'm trying to use something that is already in R. Thanks for your help in advance, Kosuke

Hi, What Lapack routine(s) should I use to calculate the determinant of a symmetric matrix of real numbers? I would appreciate any guidance on this issue. Thanks, Kosuke --------------------------------------------------------- Kosuke Imai Office: Corwin Hall 041 Assistant Professor Phone: 609-258-6601 (Direct) Department of Politics Fax: 609-258-1110 (Department)

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,

I use mnp to run a multinominal probit regression model, but the summary doesn't contain the model statistics, such as the log-likelihood and degree of freedom, for the assessment of the goodness-of-fit of the fitted model. Is there any way that I can generate these statistics for the fitted model in R? Many thanks in advance! SC

Hi All, Can the MNP package available in R be used to analyze panel data as well? *i.e., *if there are 3 observed discrete choices for three time periods for the same individual , can i estimate a panel multinomial probit model which allows correlated errors across time periods and individual heterogeneity (random coefficients) using the MNP package? In the case that it doesn't work, is

Hi, I've recently purchased PowerBookG4 (panther) and installed RAqua 1.8.1. I also installed gcc version 3.3 through Xcode tools. But, for some reason, I'm having a hard time getting gcc work with R. For example, I get the following error while installing Hmisc package. I would appreciate any suggestion to fix this problem. Thanks Kosuke * Installing *source* package

What is the current state of the R-art for ordered probit models, and more esoterically is there any available R strategy for ordered cauchit models, i.e. ordered multinomial alternatives with a cauchy link function. MCMC is an option, obviously, but for a univariate latent variable model this seems to be overkill... standard mle methods should be preferable. (??) Googling reveals that spss

Hello, I want to start testing using the MNP probit function in stead of the lrm function in my current experiment. I have one dependant label and two independent varaibles. The lrm is simple model <- lrm(label ~ val1 + val2) I tried the same thing with the mnp function and got an error that I don't understand model <- mnp(label ~ val1 + val2) I get back an immediate error that

Does anybody know how to do multiple logit/probit analysis with R? Thanks in advance!

Dear Oscar, and any other R-project person, Can you please help me to figure out the meaning of the following error message in red ? Error in eval(predvars, data, env) : numeric 'envir' arg not of length one I computed ordered logit models using 'polr' in R (I just followed the guidance a handout I found on princeton.edu about logit, probit and multinomial logit models) . The

Dear everybody! Are there algorithms for multinominal logit/probit available for R? Is it my fault that I cannot find these in CRAN? Has somebody programmed these? with best wishes Ott Toomet Ott.Toomet at mail.ee -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

Dear All, I have some questions about probit regressions. I saw a nice introduction at http://bit.ly/bU9xL5 and I mainly have two questions. (1) The first is almost about data manipulation. Consider the following snippet ################################################## mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/binary.csv")) names(mydata) <-

Hi - I am confronting a situation where I have a set of structural equation and one or two of my responses are multinomial. I understand that sem would not deal with the unordered response. So I am thinking of the following two ways: 1. Expanding my response to a new set of binary variables corresponding to each label of my multinomial response. Then use each of these as a separate response in my

Dear All, I have been struggling to understand why for the housing data in MASS library R and stata give coef. estimates that are really different. I also tried to come up with many many examples myself (see below, of course I did not have the set.seed command included) and all of my `random' examples seem to give verry similar output. For the housing data, I have changed the data into numeric

Is there any library for fitting multinomial probit using either likelihood or the "method of simulated moments" or both. I presume it would be possible to write a family function in VGAM for the multinomial probit, but was hoping that someone has done it already. Thanking you as always. Vumani Dlamini CSO-Swaziland

Hi, does anyone have a quick answer to the question of how to carry out interval regression in R. I have found "ordered logit" and "ordered probit" as well as multinomial logit etc. The thing is, though, that I want to apply logit/probit to interval-coded data and I know the cell limits which are used to turn the quantitative response into an ordered factor. Hence, it does

Hi, I have a problem with the ordered probit model -polr function (library MASS). My independent variables are countinuos. I am not able to understand two main points: a) how to calculate marginal effects b) how to calculate the relative importance of each independent variables If required i will attach my model output. Thanks Franco

Hi all. I'm just starting to explore ordinal multinomial regression. My dataset is 300,000 rows, with an outcome (ordinal factor from 1 to 9) and five independent variables (all continuous). My first stab at it was this: pomod <- polr(Npf ~ o_stddev + o_skewness + o_kurtosis + o_acl_1e + dispersal, rlc, Hess=TRUE) And that worked; I got a good model fit. However, a variety of other