similar to: plotting predicted curves with log scale in lattice

I have a set of data frames ds1, ds2, ... each having the same columns and column names: ds1 <- data.frame(x=c(1,2,3,4), y=c(5,6,7,8)) ds1 <- data.frame(x=c(9,10,11,12), y=c(13,14,15,16)) ... and I would like to combine them into just one data frame like ds <- rbind(ds1, ds2, ...) Because there are so many of them, I will have to use a character array nms <-

I was wondering if someone can help me figure out the following: I have two patient datasets, ds1 and ds2. ds1 has fields "patid", "date", and "lab1". ds2 has "patid", "date", and "lab2". I want to find all the patids that have at least 2 dated records for each lab. I started by splitting each dataset by patid, to create ds1.list

Hello R users, When trying to fit a nonlinear mixed model to a respiration time series, I get the following error message: Error in recalc.varFunc(object[[i]], conLin) : dims [product 30] do not match the length of object [34] In addition: Warning message: In conLin$Xy * varWeights(object) : longer object length is not a multiple of shorter object length Below is an example that generates

Dear R experts, Wish you all a HAPPY NEW YEAR! How do I go about plotting (using lattice) overlays of an ID (group=ID) observed, fitted data in each panel of a multiple panel plot (each panel identified by DS1 + DS2 + DS3)? "x" variable is X1 in the accompanying section of a dataset. each individual is identified by color and Y's are identified by "pch" or "lty".

I am just starting to code in R and need some help as I am used to doing this in SAS. I have a dataset that looks like this: Chemical Well1 Well2 Well3 Well4 BOD 13.2 14.2 15.5 14.2 O2 7.8 2.6 3.5 2.4 TURB 10.2 14.6 18.5 17.3 and so on with more chemicals.... I would like to transpose my data so that it looks like this: Chemical WellID Value BOD Well1 13.2 BOD Well2 14.2 BOD Well3 15.5 BOD

Dear all, I have a multiline plot with each line labeled with a different letter. But I'm not able to make the legend display the same kind of pattern '-a-', instead the letter is overwritten by the line. A simpler legend with only the letter is not very visible and the pt.bg does nothing with letters. Any idea? plot(1:10,10:1,lty=1,type='b', lwd=2,pch='a')

I am running a two-node web cluster on OCFS2 via DRBD Primary/Primary (v8.3.8) and Pacemaker. Everything seems to be working great, except during testing of hard-boot scenarios. Whenever I hard-boot one of the nodes, the other node is successfully fenced and marked ?Outdated? * <resource minor="0" cs="WFConnection" ro1="Primary" ro2="Unknown"

I'm using scan in a script to record a series of responses of the user as a function of some graphs that I put up on the screen. A toy version would be, y <- rep(NA, 3) for (ix in seq( length(y) ) ) { y[ix] <- scan( n = 1 ) } However, if I include any code after this loop, for example, y <- rep(NA, 3) for (ix in seq( length(y) ) ) { y[ix] <- scan( n = 1 ) } y I get an error

Dear all, I would like to generate 25 numbers from 1 to 100 but I would like to have some numbers that could be more probable to come out. I was thinking of the function runif: runif(25, 1, 100) , but I don?t know how to give more weight to some numbers. Example: each number from 2 to 10 has the probability of 40% to come out but the probability of each number from 11 to 100 to come out is

Dear R experts, Did someone implemented French Curve yet? Or can anyone point me some papers that I can follow to implement it? thanks in advance for your help. Paul

Dear r-help list members, I'm experiencing problems getting type="b" (or "o" or "c") to work in llines(). Try, e.g., the following scaled-down example: x <- factor(c("a", "b", "a", "b")) y <- c(1,2,1,2) z <- factor(c("A", "A", "B", "B")) symbols <- 1:2 lines <- 1:2

Hi, I'm fitting a standard nonlinear model to the luminances measured from the red, green and blue guns of a TV display, using nls. The call is: dd.nls <- nls(Lum ~ Blev + beta[Gun] * GL^gamm, data = dd, start = st) where st was initally estimated using optim() st $Blev [1] -0.06551802 $beta [1] 1.509686e-05 4.555250e-05 7.322720e-06 $gamm [1] 2.511870 This works fine but I

I have a problem with function 'inout()' in package 'splancs' on CRAN-R Version 1.2.3 under FreeBSD4.3-STABLE. The following script produces and draws points and a polygon-surrounded area. Repeating the same script many times shows, that points on the polygon-line often, but not always, are outside of the polygon-area. library(splancs) # dataset with polygon (convex

Dear r-helpers, I downloaded http://popgen.unimaas.nl/~jlindsey/rcode/rmutil.tar (it was originally .tgz, but got unzipped by my browser). Can anyone give me detailed instructions on installing this and Lindsey's other packages on R version 2.4.0 (2006-10-03)---(powerpc- apple-darwin8.7.0, locale: C)? _____________________________ Professor Michael Kubovy University of Virginia

Hi, When I compile the construction \begin{Scode}{eval=FALSE} ?HSP \end{Scode} with Sweave and latex, it outputs in the pdf as, > `?` (HSP) which is not incorrect but a bit more formal than I wanted for demonstrating the use of the help shortcut. I would like the output to look like, > ?HSP but I can't seem to make this work. I have also tried the results=verbatim argument.

grDevices::convertColor has arguments 'from' and 'to' which can take on value 'XYZ'. Can someone confirm that 'XYZ' is the same as the CIE chromaticity coordinates that are also sometimes refered to as 'xyY' in the literature? Or are these the CIE tristimulus values? It looks to me like the first case is true, but I would appreciate hearing from one of

Hi All, I am looking at trying to understand the conceptual model of how data is grouped and partitioned within a storge pool. In looking at the on disk document that Tabriz sent out a few weeks ago I see that object sets are the grouping which ZFS uses to group objects that are related. Specifially to aid in format and layout of like objects in to a set. So, for example 1 potential object

Dear lattice wizards, I am trying to figure out how to plot predicted values in xyplot, where the intercept, but not the slope, varies among conditioning factor levels. I am sure it involves the groups, but I have been unsuccessful in my search in Pinhiero and Bate, in the help files, or in the archive, or in my attempts on my own. My example follows: FACT is a factor with levels a,b,c

Dear R users, I have a problem with reshaping data. I know such questions have been asked before, but I can't get it right, neither with the reshape function nor with the melt function. My dataset has about 407 variables and about 48000 cases. Each case looks as follows: V1 v2 v3 v4 v5 v6 v7 x1 y1 x2 y2 .... x200 y200 V1 is unique, v2-v7 are

Must packages in the Depends field of the DESCRIPTION file have NAMESPACES? I haven't seen this explicitly indicated anywhere. I am writing a small package and find that when I add the abind package to the list of the Depends field, I get an error in R CMD check of the build. * checking package name space information ... OK * checking package dependencies ... ERROR Packages required but not