similar to: how to create analog stripchart plots of x vs t (t=mm/dd/yyyy hh:mm:ss)

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 =

Dear R-forum, I am looking for a good resource/help on working with POSIXct values and controlling the pretty x-axis labels and tick marks for a data VS time plots. Specifically, I wish to do programming logic which creates different vertical ablines calculations based on the range of times which i am working on. The default plot results are adequate, but I would love to make explicit calls on

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

Hello, On Mac OS X, certain Aqua/Quartz UI functionality requires an application to be launched from within an app bundle, or (alternatively) requires a Carbon application with a resource fork. Playing with the wxWidgets distribution, I discovered that it is quite easy and transparent to make such a Carbon app from (I guess) any command line application. When applied to the R executable called

Hello, On Mac OS X, certain Aqua/Quartz UI functionality requires an application to be launched from within an app bundle, or (alternatively) requires a Carbon application with a resource fork. Playing with the wxWidgets distribution, I discovered that it is quite easy and transparent to make such a Carbon app from (I guess) any command line application. When applied to the R executable called

Hi all, I'm handling massive data.frames and matrices in R (30000 x 400). In the 1st column, say, I have 0s and 1s indicating rows that matter; other columns have probability values. One simple task I would like to do would be to get the column mean values for signaled rows (the ones with 1) As a very fresh "programmer" I have build a simple function in R which should not be very

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

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

I''m not using ferret because the search I need is not that complicated. I created a basic active record search. I''m using some code from the pragmaticprogrammer book. This is the issue: I can get the single keyword to work fine when entered into the search box, but when you put to keywords separated by a space the search returns no results. It makes sense since the function

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,

Hi Usually "aggregate" is used to calculate things such as the sum of all data on the first day, the sum next day, and so on. But how can I calculate the mean of the first hour of all days, the mean of the second hour of all days, and so on. ??? That's Most examples: today at 1am + today at 2am + today at 3am +.... -> sum today tomorrow at 1am + tomorrow at

This is probably buried somewhere in the R help archives, but I've been unable to find it, so perhaps the keywords I use here will help bring the topic to the surface more easily for future users. I want to write my own modeling function (ultimately for some multidimensional windowing - but this question is on scripting basics). For purposes of figuring out my needs, lets just consider

"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

I have the attached class that I''m writing. The problem that I''m running into is that I can not access the options from the createArray function which get called after the ajax request gets done. I want to move the values of the xml file to an array and story it in the options variable. Can someone explain what I''m doing wrong? var LeaderInfo = Class.create();

Hello, I have a data frame with 1425 observations, 539 of which are zeros. I am trying to fit the following ZINB: f3<-formula(Nbr_Abs~ Zone * Year + Source) ZINB2<-zeroinfl(f3, dist="negbin", link= "logit", data=TheData, offset=log(trans.area), trace=TRUE) Zone is a factor with 4 levels, Year a factor with 27 levels, and Source a factor with 3 levels. Nbr_Abs is counts

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 =

I have a plotting function that is plots a multi-panel plot, with the x-axis as a date and various y-axes. I would like to control the frequency of the X-axis labels, ticks and grid lines. However with the following code I get no annotation on the X-axis at all. Here is a minimal data.frame Case Days Well Stream Value 1 Observed 0 P-1 Oil 1000.807785 2 Observed 31

Hello! Please help - can't find any options how to remove very big spaces between two dates containing intraday prices plotted by plot.xts. It looks like the following: on the left side of the plot window is the first bunch of points, the same is for the right hand side and a long line connecting them in the middle. I would want to merge them (cut spaces) somehow. In any case thanks for

I have narrowed down the problem. The error Error : 'AminoAcids' is not an exported object from 'namespace:bibliospec' Error : unable to load R code in package 'bibliospec' occurs only if I try to access the data using bibliospec::AminoAcids within the initialize method of an R reference class. It does work, as far as I tested everywhere else. In other methods of a