similar to: R-help Digest, Vol 81, Issue 23

I have created a function to do something: i <- factor(sample(c("A", "B", "C", NA), 793, rep=T, prob=c(8, 7, 5, 1))) k <- factor(sample(c("X", "Y", "Z", NA), 793, rep=T, prob=c(12, 7, 9, 1))) mytable <- function(x){ xtb <- x btx <- x # do more with x, not relevant here cat("The table has been created,

Hi, I?m trying to install new package in R (version 2.4.0) under windows vista and i have problems. I always receive the same message: Erro en zip.unpack(pkg, tmpDir) : no fue posible abrir el archivo 'C:/Program Files/R/R-2.4.0/library/file2019500d/mprobit/libs/mprobit.dll' It can?t open the file. I check the compatibility with the version and is ok, I have no idea where's the problem

I have no real idea what you are trying to do, but if a table is what you want, you can probably get it using the table() function. Or, more likely, the xtabs() function. Using your example from an earlier post (adjusted to make it comprehensible to the human mind): set.seed(1000) time <- factor(rep(c("Pre","Post"),each=200)) treatment <-

Hi Rolf, No it is not. I don't know to which question did you want to respond ? I desribed everything in my first email and attached links from SO with pictures included, which are quite understandable. Cheers, Jacek wt., 27 lut 2024 o 02:29 Rolf Turner <rolfturner at posteo.net> napisa?(a): > > I have no real idea what you are trying to do, but if a table is > what you

Hi all, any chance that someone got through the installation problem of mprobit on mac os X? Stephane

i just found the following list, i wondered if anybody could add to this as i have to characterize a large data set and am new to R...the list below was so helpful....can you add to this??? Just to forestall confusion amongst those who would like to use one of the functions called "describe"... Hmisc package - describe numeric name count of observations count of missing

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working

Hello, I have been asked if it is possible for recorded calls to be flagged with a decriptive title automatically and filed. The application is a third party call center operation, where certain customers that engage the call center want all calls recorded and then a submission of call samples at the end of the calling period. This is being done by hand at the moment. I fully expect that I

Hi, I've been trying to use optim to minimise least squares for a function, and then get a guess at the error using the hessian matrix (calculated from numDeriv::hessian, which I read in some other r-help post was meant to be more accurate than the hessian given in optim). To get the standard error estimates, I'm calculating sqrt(diag(solve(x))), hope that's correct. I've found

Dear R users, I would like to make my R code for MCMC faster. It is possible to integrate C code into R but I think C is too complicated for me. I would need a C introduction only for MCMC and I do not know if such a thing exists. I was thinking of Python (and scipy). Where could I read about its integration into R ? How developed are the statistical packages in Python ? I could not find a

Hi I am trying to recover the hessian of a problem optimised with box-constraints. The problem is that in some cases, my estimates are very close to the boundary, which will make optim(..., hessian=TRUE) or optimHessian() fail, as they do not follow the box-constraints, and hence estimate the function in the unfeasible parameter space. As a simple example (my problem is more complex though,

Hi all, After writing data in MMF(Memory Map File) using SEXP structure, can i reference in R? If input data is larger than 2GB, Can i reference MMF Data in R? my work environment : R version : 2.11.1 OS : WinXP Pro sp3 Thanks and best regards. Park, Young-Ju from Korea. ---------[ ???????? ???????? ???????? ]---------- ???????? : R-help Digest, Vol 89,

Hello R-help, I need to compute matrices of first derivatives of a covariance matrix C with entries given by c_ij=theta*exp(-0.5* sum(eta*(x[i,]-x[j,])^2)), wrt to elements of eta, a m-dimensional vector of parameters, given a n*m data matrix x. So far, I have been computing matrices for each parameter (given by par[index]) analytically, using the following kmatder<- function(x, par, index) {

Hello, I noticed a strange thing when attempting to upgrade a specific package (lavaan) from c2d4u and wondered if someone could confirm the problem. In short, apt seems to think that an older version from the "universe" repo is higher than the newer version from c2d4u. When I do apt-cache showpkg r-cran-lavaan I get the output at the bottom of this email. Then, I tried to force

I'm trying to obtain numerical derivative of a probability computed with mvtnorm with respect to its parameters using grad() and jacobian() from NumDeriv. To simplify the matter, here is an example: PP1 <- function(p){ thetac <- p thetae <- 0.323340333 thetab <- -0.280970036 thetao <- 0.770768082 ssigma <- diag(4) ssigma[1,2] <- 0.229502120

Does anybody know of a function that implements the derivative (gradient) of the multivariate normal density with respect to the *parameters*? It?s easy enough to implement myself, but I?d like to avoid reinventing the wheel (with some bugs) if possible. Here?s a simple example of the result I?d like, using numerical differentiation: library(mvtnorm) library(numDeriv) f=function(pars, xx, yy)

Hi guys , Im trying to do principal component analysis in R . There is 2 ways of doing it , I believe. One is doing principal component analysis right away the other way is standardizing the matrix first using s = scale(m)and then apply principal component analysis. How do I tell what result is better ? What values in particular should i look at . I already managed to find the

hi everyone, i am having difficulties with replacing the dates format in R for exporting the data set... eg: the code that i used was toms_dat<- replace(toms_dat, toms_dat ==2009-08-06, 2) toms_dat<- replace(toms_dat, toms_dat ==2009-08-04, 1) but when i export the data as into txt file or excel file the dates come up with very large numbers .....:drunk: please help me ...=) -- View

Hi, I have a scalar valued function with several variables. One of the variables is restricted to be non-negative. For example, f(x,y)=sqrt(x)*exp(y), then x should be non-negative. I need the gradient and hessian for some vector (0,y), i.e., I need the gradient and hessian at the boudary of parameter space. The "numderiv" package does not work, even for f(x)=sqrt(x), if you do

Hi, The R CMD check is successful in R 3.0.1 but fails to install package lmerTest under R-devel r63910, Here is what I get: ** preparing package for lazy loading Error in reconcilePropertiesAndPrototype(name, slots, prototype, superClasses, : no definition was found for superclass "merMod" in the specification of class "merModLmerTest" In DESCRIPTION file I have: