similar to: New Package: multinomRob

"Matching" version 0.48 is now available on CRAN. Matching provides functions for estimating causal effects by multivariate and propensity score matching. The package includes a variety of univariate and multivariate tests to determine if balance has been obtained by the matching procedure. These tests can also be used to determine if an experiment or quasi-experiment is balanced on

"Matching" version 0.48 is now available on CRAN. Matching provides functions for estimating causal effects by multivariate and propensity score matching. The package includes a variety of univariate and multivariate tests to determine if balance has been obtained by the matching procedure. These tests can also be used to determine if an experiment or quasi-experiment is balanced on

I'm interested in doing multinomial logistic regression with equality constraints on some of the parameter values. For example, with categorical outcomes Y_1 (baseline), Y_2, and Y_3, and covariates X_1 and X_2, I might want to impose the equality constraint that \beta_{2,1} = \beta_{3,2} that is, that the effect of X_1 on the logit of Y_2 is the same as the effect of X_2 on the

Hi, I would like to use the multinomRob function to test election results. However, depending on which independent variables I include and how many categories I have in the dependent variable, the model cannot be estimated. My data look like this (there are 68 observations): > head(database) RESTE09 GAUCHE09 PDC09 PLR09 UDC09 MCG09 RESTE05 GAUCHE05 PDC05 D1 1455

Dear everyone, I am trying to run rgenoud on several chips simultaneusly. I used the instructions provided on Jasjeet Sekhon's Homepage (http://sekhon.berkeley.edu/rgenoud/multiple_cpus.html). However, I have the newer version of R (R 2.12) installed - for a 64-bit machine. So, when I tried to install the special version of "snow" from a zip file provided by Jasjeet on his page, R

I'm interested in analysing some of my data using multinomial regression. I have been using nnet's multinom so far. However, I found that some of the data shows overdispersion and hence want to change to robust multinomial regression, package: multinomRob I have succesfully implemented Agresti's (2002) alligator example (chapter 7, p 268) using the option MLEonly=TRUE as there are too

I would like to limit the significant figures of the calibrated parameters determined by genoud() in the Rgenoud package. Below is some example output, where column 1 is model run number, columns 2-7 are the parameter values, and columns 8-12 are model fit statistics. I would like genoud to internally limit parameters to 4 decimal places as shown in this output. It is clear that the function is

Dear R-help: Has anyone tried using R on the the AMD Opteron in either 64- or 32-bit mode? If so, any good/bad experiences, comments, etc? We are considering getting this hardware, and would like to know if R can run smoothly on such a beast. Any comment much appreciated. Best, Andy Andy Liaw, PhD Biometrics Research PO Box 2000, RY33-300 Merck Research Labs Rahway, NJ

I see something new and unexpected here. > update.packages() trying URL `http://cran.r-project.org/src/contrib/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 163467 bytes opened URL .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... ......... downloaded

Hello all, I'm trying to use the user-created multinomRob to make some models for my data. While documentation for that function is fine and I think I'm using it correctly, I'm getting the following error when I try to use my lists of variables. data <- read.csv("data.csv", header=FALSE) subj1 <- data.frame(radius=data$V3[9:11], x1=data$V4[9:11], x2=data$V5[9:11],

Hello, I am trying to do model autocalibration using the snow and rgenoud packages. The function I want to run in task-parallel fashion across multiple machines is one that pre- and post-processes data and runs an external model code. My problem is that external file I/O is happening only in the master node and not in the slaves. I have followed Jasjeet Sekhon's suggestion to test the

Dear Friends, I have been trying to learn how to use the derivative free optimization algorithms implemented in the package RGENOUD by Mebane and Sekhon. However, it does not seem to work for reasons best described as my total ignorance. If anybody has experience using this package, it would be really helpful if you can point out where I'm making a mistake. Thanks in advance Anup Sample

I haven't seen this cryptic warning before: > update.views('Robust') Warning message: In update.views("Robust") : The following packages are not available: covRobust, distr, FRB, MASS, mblm, multinomRob, mvoutlier, quantreg, RandVar, rgam, RobAStBase, robfilter, RobLox, RobRex, robust, RobustAFT, robustbase, ROptEst, ROptRegTS, rrcov, sandwich, wle >

Dear All I am using rgenoud to solve the following maximization problem: myfunc <- function(x) { x1 <- x[1] x2 <- x[2] if (x1^2+x2^2 > 1) return(-9999999) else x1+x2 } genoud(myfunc, nvars=2, Domains=rbind(c(0,1),c(0,1)),max=TRUE,boundary.enforcement=2,solution.tolerance=0.000001) How can one increase the precision of the solution $par [1] 0.7072442 0.7069694 ? I

Hello! I need to purchase a new box, which I would like to optimize for good R performance. For the record, I will run Fedora Core 5 as and OS, and I wanted to know if anyone has experience with how the following affects R performance: - Is there a big advantage to having a 64-bit CPU over having a 32-bit? - Does an Opteron offer any advantages over an Athlon, and if yes, does it justify an

I have just uploaded an updated version of my boolean package (v1.05), which should be propagating through CRAN's mirrors soon. Boolean permits estimation of Boolean logit and probit models (see Braumoeller (2003), full reference in help file, for derivation). Boolean logit and probit are a family of partial-observability n-variate models designed to permit researchers to model causal

I have just uploaded an updated version of my boolean package (v1.05), which should be propagating through CRAN's mirrors soon. Boolean permits estimation of Boolean logit and probit models (see Braumoeller (2003), full reference in help file, for derivation). Boolean logit and probit are a family of partial-observability n-variate models designed to permit researchers to model causal

Dear R makers and users. I summarize answers to my question. Thanks for your help. The conclusion seems to be that, in terms of performance with large datasets, Matlab=Octave > R > Splus5.1 > Splus5.0 but Matlab/Octave lack many of the stat functions of R/S, and, R does not have as many time-series functions as S+ (but see last message to r-announce by adrian.trapletti at

Hi R-masters I need yours help about a problema in one of may ongoing researchers. In my research the subjects (20 in total) answer 60 questions (20 type G, 20 type S and 20 type P). Which questions is classified about 3 factor (2 level each) and the subject score with 2 scale (not integer value is possible but rare): Val range -7 to 7 and other Car range 1 to 7. This a code to fake database

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hello, Dovecot v1.0.0 deliver erases the environment if DEBUG is set, hence, also (probably) erases SENDMAIL_PATH if it has been read from configuration file. This happens with: Debian Etch, libc-2.3.6.so, gcc (GCC) 4.1.2 20061115 (prerelease) (Debian 4.1.1-21). Problem in log: May 10 12:33:07 ux-2s11-9 deliver(dvtest): execv() failed: No such