similar to: Counting question

Hi, I am interested in implementing a special variant of balloonplot.  Let me explain with an example dataset from the reference manual : library(gplots) data(Titanic) dframe<-as.data.frame(Titanic) survived<-dframe[dframe$Survived=="Yes",] attach(survived) balloonplot(x=Class,y=list(Age,Sex),z=Freq,sort=TRUE,show.zeros=TRUE,cum.margins=FALSE,             main="BalloonPlot :

Dear Group, I have the following data matrix which is a timeseries. > dput(tData) structure(list(A = c(0.2, 0.13, 0.05, 0.1, 0.02, 0.18, 0.09, 0.06, 0.13), B = c(0.15, 0.06, 0.09, 0.02, 0.03, 0.12, 0.01, 0.15, 0.06), C = c(-0.1, 0, -0.07, -0.06, -0.05, -0.05, -0.06, -0.08, -0.07), D = c(-0.15, -0.05, -0.1, -0.03, -0.13, -0.04, -0.1, -0.04, -0.15), E = c(-0.17, -0.16, -0.08, -0.07, -0.09,

Hi, I am trying to configure two identical systems with the following setup. dom0: Centos 6 OS on Apple Xserve i7 server with PCI cards for 4GB FC (LSI FC949ES) and 10GB Ethernet (Intel 82598EB) dom1: Centos 5 OS with passthru mode of PCI 4GB FC and 10GB Ethernet (ixgbe and mptfc blacklisted in dom0) Everything starts ok, but networking in dom1 using the 10GB interface has extremely high rtt

Is there a way to create a 'bubble plot' in R? For example, if we define the following data frame containing the level of y observed for 5 patients at three time points: time<-c(rep('time 1',5),rep('time 2',5),rep('time 3',5))

Hi, I want to take a look at the sourcecode for balloonplot. I would appreciate it if I could get help on overcoming the following problem : > methods(balloonplot) [1] balloonplot.default* balloonplot.table* ? ? ?Non-visible functions are asterisked > balloonplot.default Error: object 'balloonplot.default' not found > How do I access the non-visible functions? Thanks, Ravi??

Greetings, I wonder if someone could point me towards a more elegent solution than what I"ve kluged together. I have a vector "samp1" of 296 integers. They are sorted in ascending order and the numbers range from 177 to 228,953. I'd like to specify N non-overlapping intervals covering the range from 0 to 229,354 and then for each range, count the number of integers from samp1

Hi, I have tuples of data in rows of a data.frame, each column is a variable for the 'items' (one per row). One of the variables is the 'size' of the item (row). I would like to cut my data.frame into groups such that each group has the same *total size*. So, assuming that we order by size, some groups should have several small items while other groups have a few large

Hi, Fairly new to R - have done basic plots but now faced with plotting a matrix/table of results -I know what I want but cannot find out how to do it. Basically have individual questions ( x) to which an organization can rate themselves 1-10 (y) what I want to show is a matrix/density type plot (like the matrix corrolation plots I have seen on R graph site) showing for eac question (x) a

I would like to estimate a 95% highest density area for a multivariate parameter space (In the context of anova). Unfortunately I have only experience with univariate kernel density estimation, which is remarkebly easier :) Using Gibbs, i have sampled from a posterior distirbution of an Anova model with k means (mu) and 1 common residual variance (s2). The means are independent of eachother, but

I'm not understanding something. I'm trying to add xlab & ylab to a balloon plot of a table object. From docs I thought following should work: require(gplots) # From balloonplot example: # Create an example using table xnames <- sample( letters[1:3], 50, replace=2) ynames <- sample( 1:5, 50, replace=2) tab <- table(xnames, ynames) balloonplot(tab)

On Fri, Nov 17, 2017 at 9:14 AM, <m.roth at 5-cent.us> wrote: > dominic adair-jones wrote: >> going to run journalctl this evening when i get in and relay any errors i >> see. >> >> On Thu, Nov 16, 2017 at 6:01 PM, Pete Biggs <pete at biggs.org.uk> wrote: >>> On Thu, 2017-11-16 at 22:45 +0000, dominic adair-jones wrote: >>>> Ok

going to run journalctl this evening when i get in and relay any errors i see. On Thu, Nov 16, 2017 at 6:01 PM, Pete Biggs <pete at biggs.org.uk> wrote: > On Thu, 2017-11-16 at 22:45 +0000, dominic adair-jones wrote: >> Ok that's what I figured Ive narrowed it down to Plymouth but I haven't >> found much info on what the fix is. > > No, plymouth is the process

Here it is: read.inputs<-function(infile) { for (counter in 1:length(input.list)) { seek(infile,where=0,origin='start') newline<-readLines(infile,n=1) while(length(newline)>0) { if(!is.na(grep(as.character(input.list[[counter]][1]),newline)[1])) { break } newline<-readLines(infile,n=1) } if (length(newline)>0)

greetings all. running centos 7. i recently performed an upgrade and the server rebooted later in the night. now everytime i start my server its sits at the grey gnome background. i can hit ctl+atl+f2 to get to another console and the error message states "a start job is running for wait for plymouth boot screen to quit". i can ssh into the server but i dont see any obvious issues. this

Dear All Sorry for what appears a trivial matter - I'm new to R and am stumbling ahead. I have a table of numerical data (36 rows by 12 columns) such as below: GM1 GM2 GM3 GM4 GM5 ...etc GM12 Run1 1 2 1 2 3 ... Run2 2 1 3 2 1 ... ... Run36 2 1 1 1 1 I would like to plot simple line graphs of some of the runs or

Dear R users, I hav two basic data manipulations questions that I can't resolve. My data is a data frame which look like the following : id type 10002 "7" 10061 "1" 10061 "1" 10061 "4" 10065 "7" 10114 "1" 10114 "1" 10114 "4" 10136 "7" 10136 "2" 10136 "2" First, I

dominic adair-jones wrote: > On Fri, Nov 17, 2017 at 9:14 AM, <m.roth at 5-cent.us> wrote: >> dominic adair-jones wrote: >>> going to run journalctl this evening when i get in and relay any errors >>> i see. >>> >>> On Thu, Nov 16, 2017 at 6:01 PM, Pete Biggs <pete at biggs.org.uk> wrote: >>>> On Thu, 2017-11-16 at 22:45 +0000,

I am running R version 2.15.1 in Windows XP I am having problems with a function I'm trying to create to: 1. subset a data.frame based on function arguments (colname & parmname) 2. rename the PARMVALUE column in the data.frame based on function argument (xvar) 3. generate charts plotvar <- function(parentdf,colname, parmname,xvar,yvar ){ subdf <-

I don't see where describes the implementation of '[]'. For example, if x is a matrix or a data.frame, how the lookup of 'colname1' is x[, 'colname1'] executed. Does R perform a lookup in the a hash of the colnames? Is the reference O(1) or O(n), where n is the second dim of x?

I don't see where describes the implementation of '[]'. For example, if x is a matrix or a data.frame, how the lookup of 'colname1' is x[, 'colname1'] executed. Does R perform a lookup in the a hash of the colnames? Is the reference O(1) or O(n), where n is the second dim of x?