search for: xcols

This code works: x<-letters[1:6] ycols<-23:28 xcols<-rep(c(3,4,5,8),each=length(ycols)) somertime<-function(i,j)somers2(Pred_pres_a_indpdt[,i,,], population[,j]) results<-mapply(somertime,xcols,ycols) How can I make variable "h" work? x<-letters[1:6] ycols<-23:28 xcols<-rep(c(3,4,5,8),each=length(ycols)) somertime&l...

Hi All! I am desperately needing some help figuring out how to calculate LD50 with a GLMM (probit link) or, more importantly, the standard error of the LD50. I conducted a cold temperature experiment and am trying to assess after how long 50% of the insects had died (I had 3 different instars (non significant fixed effect) and several different blocks (I did 4 replicates at a time)=

Hi, I do not have much R experience just the basics, so please excuse any obvious questions. I would like to create bubble plot that have Categorical data on the x and y axis and then the diameter if the bubble the value related to x and y. Attached to the email is a pic of what I would like to do. I do hope someone can help me. -- Regards/Groete/Mit freundlichen Gr??en/recuerdos/meilleures

...> tab<-c(1,1,3,4,6,6,3,5,7,67,5,6,65,3,5,1,5,42,3,567,6,4,7,7) > tab<-matrix(tab,6,4) And try to use the function: > K_MEANSR(tab,centers=c(2,4)) [1] "AA" [1] "AAA" [1] "A" [1] "B" Error in .C("K_MEANSC", xrows = as.integer(xrows), xcols = as.integer(xcols), : "C" function name not in load table Everything that is printed on the screen is correct, but why does it says that 'K_MEANSC' function is not in load table??? It then just stops at that stage of the .R function. Thank you all for your time, Ma...

...ows: Minimise, over 100?1 real vectors v, and over scalars q >= 0, q such that, for i=1,...,100 v_i<=q v_i>=-q X'v=e_2 Here is my RGLPK code: ......................................................................... X <- # See end of this message for the X data XROWS <- 100 XCOLS <- 2 e_2=rep(0,times=XCOLS) e2[2]<- 1 obj <- c(rep(0,XROWS),1) # coefficients on v_1, . . . , v_100, q. mat <- matrix(rbind(cbind(diag(XROWS), rep(-1,XROWS)), cbind(diag(XROWS), rep(1,XROWS)), cbind(t(X), rep(0,XCOLS)), cbind(t(rep(0,XROWS)), 1)), nrow=2*XROWS+XCOLS+1) dir &...

Hello all. I am trying to run PAN, multilevel multiple imputation program, in R to impute missing data in a longitudinal dataset. I could successfully run the multiple imputation when I only imputed one variable. However, when I tried to impute a time-varying covariate as well as a response variable, I received an error message, “Error: subscript out of bounds.” Can anyone tell if my commands

Dear alltogether, I tried pan() to impute NAs for longitudinal data. The terminology in the following output follows the pan manpage. No data are attached to this script as this may be too huge. y = 15 responses pred = at first just intercept was tried (later on covariates should follow) subj = 168 different subjects with 4 to 6 observations for each subject at time points t1, t2, ..., t6 #

Dear R users I use Windows XP, R2.5.1 (I have read the posting guide, I have contacted the package maintainer first, it is not homework). In a research project on renal cell carcinoma we want to compute Harrell's c index, with optimism correction, for a multivariate Cox regression and also for some univariate Cox models. For some of these univariate models I have encountered an error

Hi, I've tried to run the multiple imputation for longitudinal data using Pan in R. The trimmed data consist 10 individuals across 4 time points. Following the example in panex.R, I imputated the model with one y variable and only random intercept. It worked well. The next step for me is to imputate a model with one y variable and both random intercept and slope. The program ran well, but

Hi, i am working with large data frames with many dependend variables. I want to write some functions that will allow me to quickly select variables from the frame and plot them in various colors depending on factor columns, possibly selecting rows according to factor conditions. In order to do this in a nice function, i need to understand how to work with a column name in the body of a

Hi, I am using lmer to analyze habitat selection in wolverines using the following model: (me.fit.of <- lmer(USED~1+STEP+ALT+ALT2+relM+relM:ALT+(1|ID)+(1|ID:TRKPT2),data=vdata, control=list(usePQL=TRUE),family=poisson,method="Laplace")) Here, the habitat selection is calaculated using a so-called discrete choice model where each used location has a certain number of alternatives

biplot could benefit from allowing colour palettes, eg. allowing col=list(xcol= xxpal, ycol= yypal) where xxpal and yypal are palettes. For an example, see the robust pricipal components in the principal componetent section of <http://www.statlab.uni-heidelberg.de/data/olive/olive10.pdf> The required change is to replace col[1L] resp. col[2L] by col[1L]] reep. col[[2L]] for example in

I have written a function which returns an "incorrect number of subscriptions error" and am unable to identify why this should happen. Any help would be gratefully received. The problem: I would like to generate combinations/permutations across different selections - for example all the combinations of "3 chosen from 6" combined with "5 chosen from 8" combined with

Hello all, I am working on a longitudinal study of children in the UK and trying the PAN package for imputation of missing data, since it fulfils the critical criteria of taking into account individual subject trend over time as well as population trend over time. In order to validate the procedure I have started by deleting some known values ?we have 6 annual measures of height on 300 children

Dear R-List, I apologize for not posting a reproducible example - the reason is that I actually do not succeed in reproducing my specific problem with generated data. Let me still describe the problem: I want to impute missing data using the "pan" package. a) It works, when I use a fraction of my data (e.g. 200 out of 44000 cases) b) It works, when I generate a dataset of equal

Dear all, I'm used to draw bubble plots (gstat) to get a first view of my spatial marked data, but I can't find a way to label legend with marks after having replaced them by a numeric scale. I have a data frame with numeric coords and factors: > names(data) [1] "x" "y" "bloc" "sub" "inoc"

Hi, I'm new to this mailing list so apologies if this is too basic. I have confocal images 512x512 from which I have extracted x,y positions of the coordiates of labelled cells exported from ImageJ as a.csv file. I also have images that define an underlying pattern in the tissue defined as areas of different pixel values 0 or 255 (also 512x512) I've exported these images as .txt

hi everybody I wonder if there is a simple way, but not simple would be ok too, to customize info/welcome page at session start time? what I'd like to do is to put together simple short howto / dos & don'ts page for users, I'm thinking it would be great if it was possible many thanks [[alternative HTML version deleted]]

...table Loading required package: data.table data.table 1.7.10 For help type: help("data.table") data.table 1.7.10 For help type: help("data.table") *** caught segfault *** address 0x2ae93df90000, cause 'memory not mapped' Traceback: 1: .Call("dogroups", x, xcols, o__, f__, len__, jsub, SDenv, testj, byretn, byval, i, as.integer(icols), i[1, ivars, with = FALSE], if (length(ivars)) paste("i.", ivars, sep = ""), is.na(nomatch), verbose, PACKAGE = "data.table") 2: `[.data.table`(DT, , sum(sharing), by = "ID1,ID2") 3...

Dear all, I am trying to make a series of waffle plot-like figures for my data to visualize the ratios of amino acid residues at each position. For each one of 37 positions, there may be one to four different amino acid residues. So the data consist of the positions, what residues are there, and the ratios of residues. The ratios of residues at a position add up to 100, or close to 100 (more on