similar to: multilevel factor model in lmer

-- R Help List -- I am looking for a bivariate normal cdf routine in R. I have some fortran routines for this, which appear to be based on 15-point quadrature. Any guidance/suggestions on making these in loadable R-functions would be appreciated. Thanks, Dan =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= Daniel A. Powers, Ph.D. Department of Sociology University of Texas at Austin

I hope this is enough information to determine the problem. Thanks in advance for any help. Configure goes ok (I think) ./configure --prefix=$HOME --without-iconv R is now configured for sparc-sun-solaris2.9 Source directory: . Installation directory: /home/dpowers C compiler: gcc -g -O2 Fortran 77 compiler: f95 -g C++ compiler: g++

R-help -- I built R-2.2.1 in my own directory on a sun (solaris). Now I would like the sysadmin to move the contents to /usr/local/lib and place the binary in /usr/local/bin. No problem. However, the RHOME variable defaults to the directory from which R was built so it is not usable by anyone but me or ROOT. I would like to avoid building this again if possible. Any ideas? Thanks, Dan

Hi all; I recently have been used 'maxLik' function for maximizing G2StNV178 function with gradient function gradlik; for receiving this goal, I write the following program; but I have been seen an error  in calling gradient  function; The maxLik function can't enter gradlik function (definition of gradient function); I guess my mistake is in line ******** ,that the vector  ‘h’ is

Dear R users, i would like to transform the following function from R-code to C-code and call it from R in order to speed up the computation because in my other functions this function is called many times. `dgcpois` <- function(z, lambda1, lambda2) { `f1` <- function(alpha, lambda1, lambda2) return(exp(log(lambda1) * (alpha - 1) - lambda2 * lgamma(alpha))) `f2` <-

I use "while" loop but it produces an errro. I have no idea about this. Error in "[<-"(`*tmp*`, i, value = numeric(0)) : nothing to replace with The problem description is The likelihood includes two parameters to be estimated: lambda (=beta0+beta1*x) and alpha. The algorithm for the estimation is as following: 1) with alpha=0, estimate lambda (estimate beta0

How to convert the following ms() in Splus to Optim in R? The "Calc" function is also attached. ms(~ Calc(a.init, B, v, off, d, P.a, lambda.a, P.y, lambda.y, 10^(-8), FALSE, 20, TRUE)$Bic, start = list(lambda.a = 0.5, lambda.y = 240), control = list(maxiter = 10, tol = 0.1)) Calc <- function(A.INIT., X., V., OFF., D., P1., LAMBDA1., P2., LAMBDA2., TOL., MONITOR.,

I am teaching myself R for use in Psych research. I don't understand the error message I am getting or how to fix it. Any suggestions will be greatly appreciated df1=read.table("fastfood.txt", header=TRUE); df1 > > c(t(as.matrix(df1))) > > r = c(t(as.matrix(df1))) # response data > > r > f=c("item1","item2", "item3") > k=3 >

Hi, My name is Laura. I'm a PhD student at Queen's University Belfast and have just started learning R. I was wondering if somebody could help me to see where I am going wrong in my code for estimating the parameters [mu1, mu2, lambda1] of a 2-phase Coxian Distribution. cox2.lik<-function(theta, y){ mu1<-theta[1] mu2<-theta[2] lambda1<-theta[3]

Hello, I'm switching over from SAS to R and am having trouble merging data frames. The data frames have several columns with the same name, and each has a different number of rows. Some of the values are missing from cells with the same column names in each data frame. I had hoped that when I merged the dataframes, every column with the same name would be merged, with the value in a complete

Hi all, I have a data.frame I received with data that look like this (comma separated strings in last row): ID Shop Items ID1 A1 item1, item2, item3 ID2 A2 item4, item5 ID3 A1 item1, item3, item4 But I would like to unbind the strings in col(2) items so that it will look like this: ID Shop Items ID1 A1 item1 ID1 A1 item2 ID1 A1 item3 ID2 A2 item4 ID2 A2 item5 ID3 A1 item1 ID3 A1 item3 ID3 A1

Dear all I want to simulate a stochastic jump variance process where N is Bernoulli with intensity lambda0 + lambda1*Vt. lambda0 is constant and lambda1 can be interpreted as a regression coefficient on the current variance level Vt. J is a scaling factor How can I rewrite this avoiding the loop structure which is very time-consuming for long simulations? for (i in 1:N){ ... N <- rbinom(n=1,

I have an error for a simple optimization problem. Is there anyone knowing about this error? lambda1=-9 lambda2=-6 L<-function(a){ s2i2f<-(exp(-lambda1*(250^a)-lambda2*(275^a-250^a)) -exp(-lambda1*(250^a)-lambda2*(300^a-250^a))) logl<-log(s2i2f) return(-logl)} optim(1,L) Error in optim(1, L) : function cannot be evaluated at initial parameters Thank you in advance -- View this

I'm performing item response theory with eRm packages I am excluding the persons that doesn't fit in the infit/outfit persons. for that I created a condition. then I have to create a new subset or matrix but with the condition. So: ORIGINAL matrix<-cbind(item1, item2, item3, item4) IF I PERFORM A head(matrix) item1 item2 item3 item4 3 2 3 1 3 1

Hello, I have two data frames. One is my dependent variable and the other is my independent variable. For each row I'd like to split the independent variable into fractiles (25 or more) and calculate the average value of the dependent variable. Then I would like to plot the average of the averages for each row for each fractile. If possible, I'd like to have the option to 1) define the

Hi, I have a question about reformatting data. It looks like it should be simple, but I've been working at it for awhile now and it's about time I ask for help. My data look like this: ITEM VALUE STEP item1 A first item2 C first item2 D second item1 A second item3 A first item3 B second item3 A third I just want to transform

I''m a newbie and I''ve been trying to figure this out for a little while now, hopefully someone can point me in the right direction. case1 <div id="new"> </div> case2 <div id="new"><div id="item1"></div></div> <div id="new2"><div id="item1"></div></div> With RJS in

Hello All, Eric Langley here with my first post to this list. I am looking to determine if R is suitable for a development project I am working on and if so possibly finding someone proficient in R that would be interested in doing the coding. I would like to preface my inquiry that while I am not a programmer I can communicate in a dialog my objectives. An array of rank ordered data looks like

Dear Friends. I found something very puzzling with constOptim(). When I change the parameters for ConstrOptim, the error messages do not seem to be consistent with each other: > constrOptim(c(0.5,0.3,0.5), f=fit.error, gr=fit.error.grr, ui=ui,ci=ci) Error in constrOptim(c(0.5, 0.3, 0.5), f = fit.error, gr = fit.error.grr, : initial value not feasible > constrOptim(c(0.5,0.9,0.5),

I posted this to the sci.math newsgroup but didn't get any responses so I was hoping someone here could help. I have a number of items with "distances" of differences between each other. What I want to do is to plot each item on a two dimensional plot such that the positions on the plot indicate the approximate distance between each item. What I want to look at, basically, is a map