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Hello, I’m trying to follow the syntax of a script from a journal website. In order to create a regression formula used later in the script, the regression matrix must have column names “X1”, “X2”, etc. I have tried to assign these column names to my matrix ScoutRSM.mat using a for loop, but I don’t know how to interpret the error message. Suggestions? Thanks, Paul

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

With the recent kernel patch viro@www.linux.org.uk[torvalds]|include/linux/ romfs_fs.h|20041006145144|23705 aka "romfs endianness annotations" utils/fstype.c no longer links because cpu_to_be32 is undefined. Options: 1) Change the header to be ok for userspace diff -ur ../linux-2.5/include/linux/romfs_fs.h linux/include/linux/romfs_fs.h --- ../linux-2.5/include/linux/romfs_fs.h

Hello all, I am working with a 1000x1000 matrix, and I would like to return a 1000x1000 matrix that tells me which value in the matrix is greater than a theshold value (1 or 0 indicator). i have tried mat2<-as.matrix(as.numeric(mat1>0.25)) but that returns a 1:100000 matrix. I have also tried for loops, but they are grossly inefficient. THanks for all your help in advance. Lanre

I have some data (from Affymetrix experiments) where I fit an aov() model to a large number of outcome variables. A reasonable fraction of the outcome variables have 0 variability because values below a cutoff have been replaced with the cutoff value (often 20) . In this case, the overall p-value from summary(lm(..)) is misleadingly small: For example (equivalent results in R 1.6.1 on both

Hi: I need help with geom_text(). I would like to count the number of Locations and put the sum of it right above each bar. x <- "Location Lake_dens Fish Pred Lake1 1.132 1 0.115 Lake1 0.627 1 0.148 Lake1 1.324 1 0.104 Lake1 1.265 1 0.107 Lake2 1.074 0 0.096 Lake2 0.851 0 0.108 Lake2 1.098 0 0.095 Lake2 0.418 0 0.135 Lake2 1.256 1 0.088 Lake2 0.554 1 0.126 Lake2 1.247 1 0.088

klibc appears to build ok, some of the apps fail gcc -Wp,-MD,.fstype.d -mregparm=3 -DREGPARM=3 -march=i386 -Os -g -falign-functions=0 -falign-jumps=0 -falign-loops=0 -nostdinc -iwithprefix include -D__KLIBC__ -DBITSIZE=32 -I../include/arch/i386 -I../include/bits32 -I../include -I../linux/include -I../linux/include2 -W -Wall -c -o fstype.o fstype.c fstype.c: In function `romfs_image':

Hello R users I like to extract z values for x1 and x2. I know how to extract coefficents using model$coef but I don't know how to extract z values for each of independent variable. I looked around using names(model) but I couldn't find how to extract z values. Any help would be appreciated. Thanks TM ######################################################### >summary(model) Call:

Hi, I was wondering if there is a way, or function in R to find confounders. For istance, > a = sample( c(1:3), size=10,replace=T) > X1 = factor( c('A','B','C')[a] ) > X2 = factor( c('Aa','Bb','Cc')[a] ) > Xmat = data.frame(X1,X2,rnorm(10),rnorm(10)) > dimnames(Xmat)[[2]] = c('z1','z2','z3','y') Now,

Good morning everyone (or maybe good evening) Is there a counterpart to the s-plus function "probplot" (which provides a qq-plot for "survreg"-objects)? Or do exist other (rather simple) possibilities to check the assumptions of the distribution? I have another question to the author(s) of summary.survreg: Why does summary(...,times=sort(x)) not give the same result as

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

Hi- I am having trouble with the syntax of looping through the rows and columns of a data frame. I have a table with 17 observations for 84 lines at n=5-10 per line. So the table is ~700x17. I want to pull out the median and stdev for each line and put it in a dataframe with rowname = linename. So I have tried the following.... #read in the table input.table <- read.table(file =

Dear All- I have a dataset that is comprised of the following: doy yr mon day hr hgt1 hgt2 hgt3 co21 co22 co23 sig1 sig2 sig3 dif flag 244.02083 2005 09 01 00 2.6 9.5 17.8 375.665 373.737 373.227 3.698 1.107 0.963 -0.509 PRE 244.0625 2005 09 01 01 2.6 9.5 17.8 393.66 384.773 379.466 15.336 11.033 5.76 -5.307 PRE 244.10417 2005 09 01 02 2.6 9.5 17.8 411.162 397.866 387.755 6.835 5.61 6.728

Hello all- I am a relatively new user of R and am working through a graduate course in Statistics that uses Minitab, SAS and some Matlab. I like using R but am having some trouble lining up the output from lda() to that of the other programs' results. The dataset below is a modified set of wine data from the Pinot Noir data set as an illustration of the 2 group LDA scenario. Mo Ba

Dear all, I'm using the latest version of the package lme4 and R version 2.7.2 (2008-08-25). After I run the model, I get the results of the model (cf. below). Then, I run an ANOVA using the "anova" function and I get the following message "Error in anova(lmer1) : Calculated PWRSS for a LMM is negative". I went trough the R-mailing list and a similar error message was

Hello! I am trying to run a GLMM using LME4, and keep getting the warning message: "In mer_finalize(ans) : false convergence (8)" I am quite new to R, and in looking into this thus far, it appears that there are a variety of reasons why this might occur, such as needing to standardize some parameters or if all subjects in one combination of parameters all have the same outcome. I also

Anybody else having problems accessing this site? Haven''t had much luck over the past couple of days. -- Posted via http://www.ruby-forum.com/.

I had found the author's (Wolfgang Viechtbauer) earlier meta-analytic code in R, MiMa, useful. so I have been exploring metafor using an example dataset from MiMa. metafor provides a lot more. However, MiMa provided parameter estimates, standard errors, z values, etc. for individual moderators in the meta-analysis, but I don't see how to obtain these from metafor. Have you any help

I am relatively new to R and am looking for advice, ideas or both... I have a data set that consists of pathogen population sizes on individual plant units in an experimental field plot. However, in order to estimate the pathogen population sizes I had to destroy the plant unit and could not determine if that plant unit became diseased or to what extent it would have become diseased. I

Hi, I would like to fit parametric survival models to time-to-event data that are left truncated. I have checked the help page for survreg and looked in the R-help archive, and it appears that the R function survreg from the survival library (version 2.16) should allow me to take account of left truncation. However, when I try the command