similar to: eRm/raschsampler error message

Dear Mr. for writing program about Gibbs sampling, i have a question. if i want to generate data from Exponential distribution but range of X is restricted, how can i do? regards, A.Rashidi   [[alternative HTML version deleted]]

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Dear list, After having upgraded from Samba-2.2.8a to Samba-3.0.4 I have problems getting "short preserve case = Yes" to work properly for filenames having only capital letters when seen from NT-4.0 explorer. A mixture of lettercase filenames and all lowercase work fine. What I see is the following: UNIX: Windows-NT: --------

I'm trying to kick off some of the rust and learn some of the R packages for Rasch modeling. When I tried using the eRm package, I get item difficulty estimates for all my items accept the first (in terms of order) item. #Begin code library(eRm) r.simulation <- sim.rasch(20,100) r.data <- r.simulation$items #eRm results erm.rasch <- RM(r.data) names(erm.rasch) erm.items <-

Hi, I am trying to do an LRSM Rasch analysis for 72-item data. 67 of the items are binary, and 5 are ternary. I have tried it with and without a specified matrix, and cannot get it to work. The primary problems I am having are: 1. Without a matrix, I get an error: Error in `rownames<-`(`*tmp*`, value = betanames) : length of 'dimnames' [1] not equal to array extent This is from

Dear useRs, new and updated features in eRm 0.9-6 for extended Rasch modeling: - infit and outfit mean-square statistics added to functions personfit() and itemfit(). - new method: plotPImap() plots a person-item map (cf. Bond & Fox, 2007), i.e., a map of locations of item (and threshold) parameters, and the distribution of person parameters. - new options in plotGOF(): 'conf':

Dear useRs, new and updated features in eRm 0.9-6 for extended Rasch modeling: - infit and outfit mean-square statistics added to functions personfit() and itemfit(). - new method: plotPImap() plots a person-item map (cf. Bond & Fox, 2007), i.e., a map of locations of item (and threshold) parameters, and the distribution of person parameters. - new options in plotGOF(): 'conf':

When I try to create a Rasch simulation of data using the sim.rasch function, I get more items than I intend #My code library(eRm) #Number of items k <- 20 #Number of participants n <- 100 #Create Rasch Data #sim.rasch(persons, items, seed = NULL, cutpoint = "randomized") r.simulation <- sim.rasch(n,k) I end up with 20 participants and 100 items, but the instructions say

Hello all, I have just started using fitting the PCM (Partial Credit Model) using eRm and have 2 problems which I cannot solve, I have checked everywhere on the net, but no joy: Firstly, I have fit a PCM model to 10 variables with differing response categories (3 for the first 6 items, 4 for the following 2 and 2 for the last two items). mat1 <- matrix(c(rasch_bart$bart_bowel,

Dear R Users, I am using the LLTM and the LRSM functions in the eRm package to do repeated measurements where there are 2 measurement points for a list of 10 items. I am trying to get ability estimates but am having trouble. I don't think that it is appropriate to use the pmat function since the person parameters are based on all 20 items. Rather, I think it would be more appropriate to

Dear R-List, I tried to fit a partial credit model using the "pcmdat" from eRm-package comparing the results of mirt, eRm, ltm and winsteps. The results where quite different, though. I cannot figure out what went wrong and I do not know which result I can rely on. This is what I did in R library(mirt) #load(file="u3.RData")

Hey people, I''m starting a new project and just finished creating the ERM diagram with about 30 tables. There are quite some tables with foreign keys so I''m not sure how to start creating the controllers/models. How should I start creating controllers/models? Should I first create all tables without foreign key? Should I just start somewhere and add them radomly? I''m

There is a weakness in the 'sample' function that is highlighted in the help file. The 'x' argument can be either the vector from which to sample, or the maximum value of the sequence from which to sample. This can be ambiguous if the length of 'x' is one. I propose adding an argument that allows the user (programmer) to avoid that ambiguity: function (x, size, replace

Following Duncan's suggestion, I forward the below to R-devel. vQ -------- Original Message -------- Subject: Re: [R] Randomly remove condition-selected rows from a matrix Date: Fri, 02 Jan 2009 10:34:52 -0500 From: Duncan Murdoch <murdoch at stats.uwo.ca> To: Wacek Kusnierczyk <Waclaw.Marcin.Kusnierczyk at idi.ntnu.no> CC: R help <R-help at stat.math.ethz.ch>

> Then the question would be if this test could be replaced with a new > argument to sample, e.g. expandSingle, which has TRUE as default for > backward compatibility, but FALSE if you dont want population to be > expanded to 1:population. It could certainly be useful in some cases, > but you still need to know about the expansion to use it. I think most > of these bugs