similar to: How to include known errors in a regression?

I want to implement the following algorithm in R: I want to split my data, use a t test to compare both means of the groups to see if they significantly differ from each other. If this is a yes (p < alpha) I want to split again (into 4 groups) and do the same procedure twice, and stop otherwise (here the problem arises). As a final result I would have different groups of data. I made some

I am trying to write a function that will simulate observed counts X and Y as below, I want the function to be able give many replicates, can somebody advise? thanks Oarabile #alpha,n sdx and sdy are constant, and N is a vector of length n. unstructured<-function(n,N,alpha,sdx,sdy){ Vx<-rnorm(n,mean=0,sd=sdx) Vy<-rnorm(n,mean=0,sd=sdy) thetax<-exp(alpha+Vx) thetay<-exp(alpha+Vy)

Hello, SAS' point and click interface has the option of produce a scatterplot with a superimposed confidence ellipse for the correlation coefficient. Since I generally like R so much better, I would like to reproduce this in R. I've been playing with the ellipse package. In order to have the points and the ellipse on the same graph I've done the following. (Load ellipse

Hi, My storage admin just assigned a Lun (fibre) to my server. Then re scanned using echo "1" > /sys/class/fc_host/host5/issue_lip echo "1" > /sys/class/fc_host/host6/issue_lip I can see the scsi device using dmesg But mpath device are not created for this LUN Pleas see below. The last 4 should be active and I think this is the problem Kernel:

I have a dataset like this: p aa index x y z sdx sdy sdz delta as ms cur sc 1 821p MET 1 -5.09688 32.8830 -5.857620 1.478200 1.73998 0.825778 13.7883 126.91 92.37 -0.1320180 111.0990 2 821p THR 2 -4.07357 28.6881 -4.838430 0.597674 1.37860 1.165780 13.7207 64.09 50.72 -0.0977129 98.5319 3 821p GLU 3 -5.86733 30.4759

Missing are capitalization/formatting of data type & function labels, as well as addressing the unit labels for the y-axis. --- src/flexchart/flexchart.mxml | 4 + src/flexchart/org/ovirt/Constants.as | 17 +++ src/flexchart/org/ovirt/charts/BarChart.as | 155 ++++++++++++++++-------- src/flexchart/org/ovirt/charts/HostChart.as | 42 ++++++-

Hello, I have simulation results in the form of Time V I 0.000000000000e+000 7.218354344368e-001 5.224478627497e-006 1.000000000000e-009 7.218354344368e-001 5.224477718002e-006 2.000000000000e-009 7.218354344368e-001 5.224477718002e-006 4.000108361244e-009 7.218354344368e-001 5.224478627497e-006 8.000325083733e-009

It is known that function bkde2D (package "KernSmooth") returns a matrix of density estimates over the mesh induced by x1 and x2. In Details it is written that "... heights of the kernel, scaled by the bandwidths, at each datapoint are summed. This sum, after a normalization, is the corresponding fhat value in the output". There are several questions: 1) How to calculate

We're using a storage solution involving two SunFire X4500 servers using DRBD to replicate a 15TB partition across the network with ocfs2 on top. We're sharing the partition from one server over NFS and the other is mounted read-only at present. The DBRD backing store is software RAID 60 on 40 disks. We've been seeing periodic issues whereby our NFS clients (Debian Lenny) are very

With Dotplot, I'm trying to make a figure that will ultimately have the same x-axis (which will be my response variable and the error bars), but the y-axis will consist of a different label for every point. Here's my code: Dotplot(fTaxonGrouped ~ Cbind(normSlope,normLwr,normUpr)|fGroup, groups=fEpoch, pch=c(17,15,19), col=c(3:1), scales = list( y = list(relation =

Dear helpers, I am using R version 2.5.1 to estimate a multinomial logit model using my own maximum likelihood function (I work with share data and the default function of R cannot deal with that). However, the computer (I have an Athlon XP 3200+ with 512 GB ram) takes quite a while to estimate the model. With 3 categories, 5 explanatory variables and roughly 5000 observations it takes 2-3 min.

Hello: I am looking at "Writing R Extensions", subsection 3.6.4, using R 1.1.0, under NT4.0, with VC++ 6.0. Under these conditions I can use the first method given for coding the out() function, but not the second, which uses getAttrib() and setAttrib(). I hope that someone will tell me how this second method can also be made to work. Details follow, for anyone kind enough to help.

Hi all, Appologies for the rather basic IO question but I am rather new to R... Migrated from IDL/Matlab recently. I have a rather simple Fortran control file (sigh...) that I am trying to parse and read using R. My problem is that the file's format is somewhat flexible. Imagine: --- 1> 39 1901 2> 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 3> 22 24 26 28 30 32 34 36

Hello, I have been exploring the possibility to transition some code that currently uses image() to use the new rasterImage(). To date, I haven't been able to specify a color look-up strategy that works. For example... nx <- 100 ny <- 100 m <- matrix(data = rep(seq(0,1, length = nx), ny), ncol = nx, nrow = ny, byrow = TRUE) plot(1:nx, 1:ny, type = "n") my.color

Hey all Im having a problem... Ok, this is the situation... I have a small product image, on which ive floated a div over it, and defined it as draggable. Now, this works, and i can drag it around no problem. great. but then, what i want to do is, based on the location of that dragable element from the top and the left, to move (using the Effect.MoveBy method) a larger image - so effective

Not many of you will use grid() widely, probably. Also, two months ago, Paul Murrell said on R-help (topic "grid command") PM>> i think the abline() solution is the best for doing what grid() won't. PM>> like you say, grid() is just a simple front-end to abline(). grid() *is* too simple to be of practical use. I propose the following which is of some practical

--k1lZvvs/B4yU6o8G Content-Type: text/plain; charset=us-ascii Content-Disposition: inline The attached patch against R 2.2.0 makes the following improvements to the all.equal() function: 1. Check names! Stock R all.equal() (unlike S-Plus) ignores names completely on some objects. I consider this wrong - if the names are different, the object is NOT "the same". 2. When a

Hello everyone, i am currently creating a barplot. This barplot takes a vector of ~200 datapoints. Each datapoint represents one bar. http://img96.imageshack.us/i/human1w.png/ (Ok as you see, it is not only one barplot, but a series of barplots). Now, these barplots represent a human chromosome. This means they are ordered. For instance bar number 50, means position 50 in the human chromosome.

Dear grid-expeRts, The goal: I would like to construct a plot (matrix) with grid and gridBase, which consists of four "sub-plots". The sub-plots should have a square plotting region as one would force with par(pty="s") in base graphics. The problem: I don't get a square plotting region, not even by specifying pty="s" in par(). Indeed, if you display the grid

Greetings -- I'm programming a data mining system in R for protein structural data. As a seasoned Perl and Python and Ada and ML, et al., programmer, I am severely befuddled by the environment problem, where data is not found in a 3rd level nested function. I did peruse the parent frame not on the search path idea, and came up with a hack which kinda works, also below with the code which