similar to: Plotting dates and grid lines on the X-Axis of xyplot

Hello r-experts, I sure could us a little help. I have an ever updating text file with timestamped data in it. I can reformat in anyway I want if need be but currently I have chosen to make columns of date, time and measuresed value (comma delimeted and with the dates and times in quotes to interpret them as strings). Here is a small section of my text data file:

Hi Wenzhi, This question would be best answered on the samba list ( I am cc'ing a copy now ) Its not a binary dependant question, otherwise I would have answered it promptly. Sorry for brushing you off, I just dont have the time to help you. I am sure someone on the samba list will be more than happy to lend you a hand. Brian Roberson brian@bstc.net -----Original Message----- From:

Hi there, In multiple regression one way to view R^2 is as (the square of) the correlation between original y's and the estimated y's. Suppose you fit a multilevel model with random intercept for each cluster. Would it be valid to compute an R^2 by using fixed effects plus the group intercepts to reduce the residuals? I suspect this has been done and, given its absence from the lmer

Dear all, I would like to use the residuals in a general linear mixed effect model to diagnose model fit. I know that the resid function has been implemented for linear mixed models but not yet for general linear mixed effects. Is there a way to get them out of lmer fit objects? I tried searching the r-help archive and found nothing. I tried and failed to replicate what (I guessed would be

I have hundreds of megabytes of price data time series, and perl scripts that extract it to tab delimited files (I have C++ programs that must analyse this data too, so I get Perl to extract it rather than have multiple connections to the DB). I can read the data into an R object without any problems. thedata = read.csv("K:\\Work\\SignalTest\\BP.csv", sep = "\t", header =

added --prefix=/usr/local/wine to CONFARGS in file). When I try to run any program with any sort of system of calling wine it exits immediately and starts the debugger with something like the following trace. I notice that the trace seems to end in a call to dl-reloc.c. I don't know if this is a bogus message produced by something else, but I did build glibc2.2.3 from source awhile ago.

Hi, A simple question I hope. I wish to add a single vertical line to a plot with several density plots. Here is a simplified example. ############ thedata <- data.frame(x1=rnorm(100,1,1),x2=rnorm(100,3,1)) #create data thedata.m<-melt(thedata) densityplot(~value, thedata.m, groups=variable,auto.key=list(columns=2)) #this gives the two density plots ######### what I wish now is to add a

In one particular situation predict.coxph gives an error message. Namely: stratified data, predict='expected', new data, se=TRUE. I think I found the error but I'll leave that to you to decide. Thanks, Chris ######## CODE library(survival) set.seed(20121221) nn <- 10 # sample size in each group lambda0 <- 0.1 # event rate in group 0 lambda1 <- 0.2 # event rate in group 1

Full_Name: Ed Borasky Version: R-beta 2.1.0 2005-04-08 OS: Linux 2.6.11 GCC 3.3.5 Submission from: (NULL) (24.21.57.139) I downloaded the latest R-beta tarball and did a build with the default options. OS is Linux 2.6.11 and compiler is GCC 3.3.5. "make check-all" failed with the following message: make[3]: Entering directory `/home/znmeb/R-beta/tests' running code in

I am running R 2.7.0 on a Suse 9.1 linux cluster with a job scheduler dispatching jobs and openmpi-1.0.1. I have tried running one of the examples at http://ace.acadiau.ca/math/ACMMaC/Rmpi/examples.html in Rmpi and they seem to be working, except mpi.close.Rslaves() hangs. The slaves are closed, but the master doesn't finish its script. Below is the example script and the call to R. The job is

Hi, I'm testing the efficiency of the Rmpi package regarding parallelization using a cluster. I've found and tried the task pull programming method, but even if it is described as the best method, it seems to cause deadlock, anyone could help me in using this method? here is the code I've found and tried: # Initialize MPI library("Rmpi") # Notice we just say "give us

Hello, # Full disclosure. I am not sure if my problem is a bug(s) in the code, or a fundamental misunderstanding on my part about what I am trying to do with these statistics. I am not familiar with maximum likelihood tests. # I currently have two vectors Aequipecten<-c(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,

I just looked at the data at the URL you posted and it looks like it consists of all the points in a rectangular grid. When you triangulate a rectangle it is arbitrary whether you use the SW-NE or the SE-NW diagonal and that looks like the only difference between the various algorithms. Bill Dunlap TIBCO Software wdunlap tibco.com On Thu, Jan 25, 2018 at 5:14 AM, Yuen, Kam <k.yuen at

"The question is, what is making the results for the R packages different from each other?" There are literally thousands of R packages, contributed independently by thousands of people. There should be no expectation of consistency or for that matter, "correctness", among them. Caveat emptor. Only within the base R distribution, maintained and mostly written by the R Core

Dear R help, What am I doing wrong here? when I don't specify the priors it works just fine but when I specify the priors it breaks.? Does anyone know why and how I can fix it? ---- > N=20000 > ncontrol=ncases=50 > X <- as.matrix(rnorm(N,0,1)) > eta <- -5.3 + X * 1.7 > p <- exp(eta)/(1+exp(eta)) > Y <- rbinom(N,1,p) > controls <- sample(seq_len(N),

Here is an example: The legends (mainly the factor level names) are cut off on the right. Somehow the internal calculation which computes horizontal space for the legend is not flexible enough. ## Call a new graphics window {with default par()s !}: get(getOption("device"))() par(mfrow = c(2,2)) ## part of example(interaction.plot) _improved_ using with() : data(OrchardSprays)

The problem: I would like to translate the Octave algorithm in griddata.m to R. Within the griddata algorithm calls are made to the Delaunay function. For the R translation I have found delaunayn within the "geometry" package and also the deldir package. Both do similar things but give slightly different results depending on the input. The question is, what is making the results for the

I'd like to access data in my R session from elsewhere via HTTP. My particular use case would be R on Linux, accessing data from Windows, all on the same intranet. Naively, when I say this, I imagine something like: > theData <- big.calculation.returning.data.frame() > startHttpServer(port=8675) (blocks until I C-c it) Elsewhere... http://linuxmachine:8675/htmlDF?theData

I am trying to plot multiple densityplots on each panel, and using panel.groups to do some additional plotting (not included in the example) as in this example. library(lattice) thedata <- data.frame(x=rnorm(1200),class=rep(1:3,each=200,times=2), group=rep(1:2,each=100,times=6)) densityplot(~x | class,groups=group, xlab='x', panel.groups =

Dear all, I want to draw ticks on the 3rd and 4th row of a lattice. How do I do this ? In my search of the help, I discovered a parameter alternating,which kind of says where the ticks will be but does not suffice for me. I am running this command : - barchart(X03/1000~time|Company, data=df1[which(df1$time!=1),], horiz=F,