similar to: Generate bivariate binomial data

Dear all, I'm not getting what I'm doing wrong. The line below from my read.fsa.bin function throws an error when just loading my AFLP package and disappears when I load the zoo package as well. #the line that throws the error Index <- which(Peak == rollmax(Peak, k = 1 + 2 * floor((min(diff(SizeStandard)) * Fs - 1) / 2), fill = -Inf)) #the error Error in UseMethod("rollmax")

Dear all, One of the functions that I wrote (ggsave.latex) extents the functionality of a function (ggsave) in another package (ggplot2). Instead of copying all the information I would like to create a link in the helpfile of ggsave.latex to the helpfile of ggsave. I tried \code{\link{ggsave}} and \code{\link{ggplot2::ggsave}}, but neither worked. Both cases gave a 'missing link' warning.

Dear all, I have a list of n matrices which all have the same dimension (r x s). What would be a fast/elegant way to calculate the element wise average? So result[1, 1] <- mean(c(raw[[1]][1, 1] , raw[[2]][1, 1], raw[[...]][1, 1], raw[[n]][1, 1])) Here is my attempt. #create a dummy dataset n <- 3 r <- 5 s <- 6 raw <- lapply(seq_len(n), function(i){ matrix(rnorm(r * s), ncol =

Dear all, I'm plotting some points on a graph where both axes need to have the same scale. See the example below. Coord_equal does that trick but in this case it wastes a lot of space on the y-axis. Setting the limits of the y-axis myself was no avail. Any suggestions to solve this problem? library(ggplot2) ds <- data.frame(x = runif(1000, min = 0, max = 300000), y = runif(1000, min =

Dear all, I get a bug in the examples of my AFLP package on R-forge (https://r-forge.r-project.org/R/?group_id=1027) but only on the Linux version. The windows version compiles. The Mac version skips the examples and compiles. The strange thing is that the packages compiles on my Ubuntu 10.10 machine with R 2.15.0. Therefore I can't reproduce the error. I have traced the problem at

Dear all, I'm documenting an elaborate analysis as a private package. The package writes all required output to a database. I use a Sweave file to transform all the results from the database into a report. Now I would like to add this Sweave to my package. I'm a bit puzzled on how to do that. It is not a vignette: the data is not available when the package is build and I need to

Dear all, I'm having troubles migrating a large matrix from one system to another. #system 1: Ubuntu 12.04, 64-bit, running R 2.15.2 # do some simulations # save the simulations > save(Output, file = "Simulations.Rdata") #Output is a numeric matrix with 6 columns and about 2M rows. Use ftp to transfer the Simulations.Rdata file to system 2 #system2: Windows XP, 32-bit running

Dear all, My package has Depends: lme4.0 in the DESCRIPTION. I need to extract the fixed effect of a model and their standard errors. I use coef(summary(model)) inside a function to do that. Model is the output of a call to glmer() from the lme4.0 package. coef(summary(model)) throws an error: $ operator is invalid for atomic vectors I have tracked it down to a problem with summary(model)

Dear all, Is it possible to incorporate a nested design in GEE? I have measurements on trees that where measured in two years. The trees are nested in plots. Each plot contains 24 trees. The number of plots is 72. Hence we would expect 2 * 24 * 72 = 3456 data points. A few are missing, so we end up wih 3431 data points. This is what I have tried until now. #assuming independence between trees

Hi all, I have managed to create a figure on the screen with multiple plots in it. Something like the example below. When I save that with ggsave(), only the last plot gets saved (pPath in the example) instead of the entire figure. Any suggestions how I can save this kind of figures automated? Thanks, Thierry library(ggplot2) pPoint <- qplot(unemploy/pop, psavert, data=economics) pPath

Dear all, I'm using zeroinfl() from the pscl-package for zero inflated Poisson regression. I would like to calculate (aproximate) prediction intervals for the fitted values. The package itself does not provide them. Can this be calculated analyticaly? Or do I have to use bootstrap? What I tried until now is to use bootstrap to estimate these intervals. Any comments on the code are welcome.

Dear all, I'm puzzled by the error I get from R CMD check one of my packages. I'm running R CMD check with the --as-cran flag and it get the error both from running it from the command line as from within Rstudio. On the same machine R CMD check on my GRTS package (https://r-forge.r-project.org/R/?group_id=1027) works fine. Any suggestions on how to fix this? I can send the source code

Dear all, I'm trying to connect to an MSAccess database (ArcGIS personal geodatabase). I keep getting an error about the channel when using sqlQuery(). However, sqlTables() does not complain about the channel and lists all tables in the database. If I try sqlFetch(), then R crashes. I'm happy to hear suggestions on how to solve this. Best regards, Thierry > MDB <-

Dear all, predict.lme() throws an error when the fixed part consists of only an intercept and using newdata. See the reproducible example below. I've tracked the error down to asOneFormula() which returns in this case NULL instead of a formula. Changing NULL instead of ~1 in that function (see below) solves the problem in the case of an intercept only model (m1). It does not solve the problem

Dear all, I'm using Roxygen for the first time and I'm getting a rather cryptic error message. I must be doing something wrong but I have no clue what is it. Any suggestions? Regards, Thierry roxygenize("AFLP", roxygen.dir = "AFLP", copy.package = FALSE, unlink.target = FALSE) Writing AFLP.outlier to AFLP/man/AFLP.outlier.Rd Writing AFLP.outlier to

Dear all, Is there an elegant way to add citations of packages when using Sweave? Ideally I'd like a function which creates a Bibtex-file with the packagenames as keys. The idea is to use \cite{packagename} or \cite{R} in LaTeX. I know you can get the Bibtex entry with toBibtex(citation("packagename")). But after updating R or a package one needs to update the bib-file too. When

Dear all, I am struggling with a problem and I am hoping that somebody could point me in the right direction. I am trying to match the locations of two peak patterns. A is the true pattern. B is the measured pattern. Hence A and B have a very strong linear relationship. The problem is that B can contain false positives: peaks due to noise instead of the true pattern from A. An additional problem

Dear Paula, There are probably missing observations in your data set. Read the na.action part of the glm help file. na.exclude is most likely what you are looking for. Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg /

I have some questions about the use of weights in binomial glm as I am not getting the results I would expect. In my case the weights I have can be seen as 'replicate weights'; one respondent i in my dataset corresponds to w[i] persons in the population. From the documentation of the glm method, I understand that the weights can indeed be used for this: "For a binomial GLM prior

Dear Thierry, thank you for the quick reply. I have only one question about the approach you proposed. As you suggested, imagine that the model we end up after the model selection procedure is: mod2.1 <- lmer(dT_purs ~ T + Z + (1 +T+Z| subject), data =x, REML= FALSE) According to the common procedures specified in many manuals and recent papers, if I want to compute the p_values relative to