similar to: xyplot 3 panels 3 different Y variables

I am trying to define a general R function that has a function as the output that depends on the user's input arguments (this may make more sense by looking at the toy example below). My real use for this type of code is to allow a user to choose from many parameterizations of the same general model. My "issue" is that when I compile a package with this type of code in it I get a

Dear friends. I wanted to reproduce a sheet of paper useful for plotting the reciprocal of some biochemical variable (creatinine) over time (Bleyer Am J Kidney Dis 34:576-578,1999). Time on X axis with units years and months. On Y axis, 1/creatinine, but with the original creatinine value indicated - to make it easier for people to use it. When using the graph, the linear decrease in 1/crea over

I''ve been using btrfs as a spool space on our back-up server to get familiar with it and things work fine until the volume fills up. Our backup software (bacula) usually spools until the volume is full, then despools and respools, etc. With btrfs, it fills up and bacula thinks there is still space so it keeps trying and then finally errors out. I thought this was a problem because I was

Dear Colleagues   I have the following code that generates a boxplot for one specific labtest:   boxplot.n(LBSTRESN~COHORT, main="Boxplot of laboratory data for XLXXX-XXX test=Creatinine", subset = LBTEST=="Creatinine", xlab = "Cohort Number", ylab = "Units = umol/L", varwidth=TRUE   I would like to know if there is a way to loop through the dataset and

Some time ago I was allowed to discuss "Diamond Graphs", and whether they would be useful in R, in this mailing list. The August 2003 issue of The American Statistician has finally arrived here and I have been able to read the article. A number of points of interest arise. 1. The article is "A Diamond-Shaped Equiponderant Graphical Display of the Effects of Two

Hi everyone, I'm trying to generate an RNA degradation plot of the Estrogen example data plot, but seem to get an error. I've tried defining an ylim value, ylim=c(0,30) , but it doesn't seem to work either. My code is as follows: > RNAdeg<-AffyRNAdeg(Data) > png(DegLoc, width=720, height=720) > par(ann=FALSE) > par(mar=c(3,3,0.1,0.1)) >

Dear friends - We have 25 rats, 14 of these subjected to partial removal of kidney tissue, 11 to sham operation, and then followed for 6 weeks. So far we have data on 26 urine metabolites measured by NMR 7 times during the observation. I have smoothed the measurements by b.splines in fda including a roughness penalty, and inspecting the mean curves for nephrectomized and sham animals indicate

I am running the sm.density.compare function amd I am getting the following error:   my code is  > sm.density.compare(LBSTRESN,COHORT,xlab="Units = umol/L"subset = LBTEST=="Creatinine")   Error in if (from == to) rep.int(from, length.out) else as.vector(c(from,  :   missing value where TRUE/FALSE needed   I do not understand the error and I have had no help when searching

I'm having trouble making contour lines for this attached, sparse dataset (low data:NA ratio!). Is it the high number of NA's, or funny layout of the densities, or something else that's causing this? This is a subsample of the dataset, and I get the same problem when using the full data. The only reason I get any contours is because I'm forcing specific levels. If no levels are

Hi all, I have a question about multiple imputation within the MICE package. I want to use passive imputation for my variable called X, because it is calculated out of multiple variables, namely Y, Z. Let's give an example with BMI. I know, that if I want to use passive imputation for BMI, I can use the following command: meth["BMI"] <- "~I(weight/(height/100)^2)"

I have : raw <- read.table("monthly.text", skip=3, sep="|", col.names=c("junk", "junk2", "wpi", "g.wpi", "wpi.primary", "g.wpi.primary", "wpi.fuel", "g.wpi.fuel", "wpi.manuf", "g.wpi.manuf",

Hello, I've tried to analyze some data with a CMH test. My 3 dimensional contingency tables are 2x2xN where N is usually between 10 and 100. The problem is that there may be 2 strata with opposite counts (the 2x2 contigency table for these are reversed), producing opposite odds ratios that cancle out in the overall statistics. These opposite counts are very important for my analysis, since

Dear list member, My question is related to input file format to an Anova from car package. Here is an example of what I did: My file format is like this (and I dislike the idea that I will need to recode it): Hormone day Block Treatment Plant Diameter High N.Leaves SH 23 1 1 1 3.19 25.3 2 SH 23 1 1 2 3.42 5.5 1 SH 23 1 2 1 2.19 5.2 2 SH 23 1 2 2 2.17 7.6 2 CH 23 1 1 1 3.64 6.5 2 CH 23 1 1 2

Below is an example of a problem I encounter repeatedly when I write functions. A call works at the command line, but it does not work inside a function, even when I have made sure that all required variables are available within the function. The only way I know to solve it is to make the required variable global, which of course is dangerous. What is the elegant or appropriate way to solve

Hi, This is not an R question, but I've seen opinions given on non R topics, so I wanted to give it a try. :) How would one treat a variable that was measured once, but is known to fluctuate a lot? For example, I want to include a hormone in my regression as an explanatory variable. However, this hormone varies in its levels throughout a day. Nevertheless, its levels differ substantially

Hi, at the moment I'm trying to understand the limma/affy Packages. I've tried every example I could find to try and understand the ways to create design and contrast matrices. I must admit though, that I can't figure it out. I did a few times the estrogen files from the book "bioinformatics and computational biology solutions using R and Bioconductor". I know it's a

Dear R experts, beginners and everyone else, I'm calculating "cumulative periodogram" using the command "cpgram" [1] from the MASS library. Here is a short example with the "lh" (hormone level) dataset: library(MASS) plot(lh,type="l",ylab="value",xlab="time", main="Hormone Levels (lh)") spectrum(lh,

Hello: Is there a way to get a mean from values stored in different rows? The data looks like this: YEAR-1, JAN, FEB, ..., DEC YEAR-2, JAN, FEB, ..., DEC YEAR-3, JAN, FEB, ..., DEC What I want is the mean(s) for just the consecutive winter months: YEAR-1.DEC, YEAR-2.JAN, YEAR-2.FEB YEAR-2.DEC, YEAR-3.JAN, YEAR-3.FEB etc. Thanks.

Full_Name: Kem Phillips Version: 2.7.1 (2008-06-23) OS: Windows Xp professional Submission from: (NULL) (98.221.200.108) The Hmisc function describe fails, giving the error message: Error in formatDateTime(dd, atx, !timeUsed) : could not find function "format.dates" Loading the chron package, where function dates apparently resides, does not fix the problem. Note

Thank you to Peter Dalgaard, who provided help for some of this solution. It is still not ideal since the dots which are equidistant in the x-direction ideally should respect the reciprocal scale in the y-direction. op <- par("cex"= 0.7) x<-y<-NA plot(x,y,xlim=c(0,10),ylim=1/c(2000,70), axes=F) box() axis(1)