similar to: Segmentation fault in estimating structural equation models with the SEM package.

Hi, I just installed the gregmisc bundle. When I do library(gdata) (or library(gtools), library(gmodels)) everything works fine. When I do library(gplots) I get Error in parse(file, n, text, prompt) : syntax error on line 1850 Error in library(gplots) : package/namespace load failed I'm using R-1.7.0 on Mac OS 10.3. Can anybody help me with this? Could I be doing

Dear all, I'm working on MAC OS X 10.4.7 using R version 2.3.1 (June 2006) and platform powerpc-apple-darwin8.6.0. Since I installed the new version of R I cannot install packages any more (but it worked fine before) and get the following message every time. I can, however, install packages from the command line if I get them as precompiled binaries.

Dear R list members, I have a question about the proper use of the typsize and fscale arguments to nlm. I use nlm in my sem package to fit general structural-equation models, which entails maximizing a multinormal likelihood with respect to parameters that represent regression coefficients and covariances of variables. The magnitudes of these parameters can be very different. The

It would be really nice if nlm took a set of "..." optional arguments that were passed through to the objective function. This level of hacking is probably slightly beyond me: is there a reason it would be technically difficult/inefficient? (I have a vague memory that it used to work this way either in S-PLUS or in some previous version of R, but I could easily be wrong.) Here's

I am trying to view the source code of the function nlm in the stats package of R 2.4.1. I downloaded the source from CRAN and opened nlm.R, and it calls a .Internal function: .Internal(nlm(function(x) f(x, ...), p, hessian, typsize, fscale, msg, ndigit, gradtol, stepmax, steptol, iterlim)) This is the same thing I saw when entering the function name at the R command

Dear R users, Please help me on using "mix" function under package "mixdist". My data distribution shows there are two components for the mixture distribution: left part is an exponential and right part is a normal. So I plan to use "gamma" mixture distribution to estimate the parameters. Here is what I am using for the "mix" function. Test<-mix(x,

Hi Everyone, Is there a simple way to force nlm to take larger initial steps? Setting print.level = 2 allows me to inspect the step size at each iteration, but I appear not to have made any appreciable impact on it by changing values of typsize, fscale, steptol or stepmax. The steps repeatedly come out tiny, 1e-9 typically, and the algorithm is terminating not because the gradient is zero (it

Adam, It seems that your attachment didn't make it through. That aside, my experience with strange errors like those (random type not implemented ones) has been that you may be looking at a memory problem on you machine. Given that you can't replicate on another platform (and the .csv file didn't come through), I would think it wise to start there. My 2c. And I love bacon too :)

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. --1660387551-1458482416-1249639718=:2997 Content-Type: TEXT/PLAIN; CHARSET=US-ASCII; FORMAT=flowed Content-ID: <Pine.LNX.4.64.0908071039211.2997 at parser.ilovebacon.org> Hello, There appears to be a bug in the nlm function, which I

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. --1660387551-150661043-1249684349=:2997 Content-Type: TEXT/PLAIN; charset=iso-8859-1; format=flowed Content-Transfer-Encoding: QUOTED-PRINTABLE Hi Jeff, =09As mentioned in my message, I *did* replicate on another platform.=20 One platform was

Dear R list members, Since today seems to be the day for optimization questions, I have one that has been puzzling me: I've been doing some work on sem, my structural-equation modelling package. The models that the sem function in this package fits are essentially parametrizations of the multinormal distribution. The function uses optim and nlm sequentially to maximize a multinormal

I am looking for study materisl?on how to conduct 'small area estimation' using structural equations models in R for both longtudinal and repeated cross-section data.?Tried google did not work. There are other regression technique my interest is on structural equation models.?

Hello, Is there a package or sample code that shows how to do ex ante forecasts with a macroeconomic structural equations model? I looked at the "sem" package, which lets you estimate e.g. Klein's model, but I'm not sure how to make simulations using the full set of equations, including the identities. Thank you, Ronaldo Carpio rncarpio at yahoo.com

Dear listers, Does anyone have any experience running marginal structural models in r or can point me in the direction of any good tutorials on this? Regards, //M

Hi all, I am using package lavaan and have created a structural equation model with two exogenous and seven endogenous variables with the following relationships #specify the model m1 = ' # regressions D ~ ma + hs + b4 + b5 + b15 + b16 ma ~ hs + b4 + b5 + b15 + b16 hs ~ b4 + b5 + b15 + b16 b4 ~ el + la b5 ~ el + la

Dear R users, Apologies for the total beginner's question. I was wondering whether you could tell me if there is a structural equation modelling function that can handle binary data i.e. in similar manner to the GLM function with a binomial family. Best wishes, Mario

Dear r-help list members, I'm teaching a one-day workshop on "An Introduction to Structural Equation Modeling with the sem Package for R" at McMaster University in Hamilton, Ontario, Canada, on November 22. The workshop is open to non-McMaster attendees at a small charge. Further information, including on how to register, is in the attached poster. Best, John

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model

`vetr` implements a declarative template-based approach to verify that objects meet structural requirements, and auto-composes error messages when they do not. This package is intended to simplify a more formal use of S3 objects. The template concept is borrowed from `vapply`: >> vet(numeric(1L), 1:3) >? [1] "`1:3` should be length 1 (is 3)" >> vet(numeric(1L),