search for: 0.0024

Dear R-tisans, I am trying to calculate the 12th root of a transition (square) matrix, but can't seem to obtain an accurate result. I realize that this post is laced with intimations of quantitative finance, but the question is both R-related and broadly mathematical. That said, I'm happy to post this to R-SIG-Finance if I've erred in posting this to the general list. I've

Using the small reproducible example below, I'd like to know if one can somehow use the matrix "sig" (defined below) to add a black outline (with lwd=2) to all pixels with a corresponding value of 1 in the matrix 'sig'? So for example, in the ggplot2 plot below, the pixel located at [1,3] would be outlined by a black square since the value at sig[1,3] == 1. This is my first

On 23.11.2012, at 15:12, john skaller <skaller at users.sourceforge.net> wrote: > > On 23/11/2012, at 5:46 PM, Sean Silva wrote: > >> Adding LLVMdev, since this is intimately related to the optimization passes. >> >>> I think this is roughly because some function level optimisations are >>> worse than O(N) in the number of instructions. >>

    I created a couple of timeSeries objects - when I was merging them , I got an error. Looking at the data , I see that one of the time series has   06/30/2007  0.0028       0.0183  0.0122      0.0042  0.0095    -          07/31/2007 -0.0111       0.0255  0.0096     -0.0069 -0.0024  0.0043       08/31/2007 -0.0108      -0.0237 -0.0062     -0.0138 -0.0173 -0.0065       09/30/2007 

Hi Eric, you can use an annotate-layer, eg ind<-which(sig>0,arr.ind = T) ggplot(m1.melted, aes(x = Month, y = Site, fill = Concentration), autoscale = FALSE, zmin = -1 * zmax1, zmax = zmax1) + geom_tile() + coord_equal() + scale_fill_gradient2(low = "darkred", mid = "white", high = "darkblue",

Hi there, I checked google for aov. usually one uses summary to see whether the p-value is small. but I want to put aov in my script. how can I get the p-value, (0.1115, 0.6665, 0.6665 in the following example)? thanks YU > datafilename="http://personality-project.org/r/datasets/R.appendix2.data" > data.example2=read.table(datafilename,header=T) > aov.ex2 =

Hi r-sers, I have a data of relative frequencies for the interval of 0-20, 20-40,...380-400.  I would like the two data on the same graph using the same x-axis label.  My question is how to get a smooth curve using kernel density code if it possible for this data.   > cbind(rel_obs,rel_gen)           rel_obs rel_gen  [1,] 0.000000000  0.0000  [2,] 0.092534175  0.0712  [3,] 0.105152471  0.1092

Hello, I am relatively new to R and I am working through the code that is provided in the book Numerical Ecology with R and I have run across an error message that I can't seem to figure out. I am using the vegan, ade4, gclus and cluster packages. The code is as follows: # Ordered community table # Species are ordered by their weighted averages on site scores or <- vegemite(spe,

Hi all, today we had a performance issue transfering a big amount of data where one file was over 50GB. Rsync was tunneled over SSH and we expected the data to be synced within hours. However after over 10 hours the data is still not synced ... The sending box has rsync running with 60-80 % CPU load (2GHz Pentium 4) while the receiver is nearly idle. So far I had no acces to the poblematic

Hello again, everytime I think I got something to work, the next issue comes up... I have the following data.frame, I want to visualize: > data_rb tld spam1 spam2 share 1 ca 826436 73452 0.0889 2 org 470550 25740 0.0547 3 de 156042 15531 0.0995 4 com 140753 7527 0.0535 5 edu 34845 2507 0.0719 6 net 12781 382 0.0299 7 ru 7648 18 0.0024

Hi, this is my first time using the nlme package, and I ran into the following puzzling problem. I estimated a mixed effects model using lme, once using groupedData, once explicitly stating the equations. I had the following outputs. All the coefficients were similar, but they're always slightly different, making me think that it's not due to numerical error. Also, what is the

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

Target: FreeBSD 6.2-STABLE on i386 autoconf says: configure:2122: checking build system type configure:2140: result: i386-unknown-freebsd6.2 [...] configure:2721: gcc -v >&5 Using built-in specs. Configured with: FreeBSD/i386 system compiler Thread model: posix gcc version 3.4.6 [FreeBSD] 20060305 [...] objdir != srcdir, for both llvm and gcc. Release build. llvm-gcc 4.2 from source.

I am getting the following errors when I am trying to plot the data below. I cannot figure out the error. Error in plot.window(...) : need finite 'xlim' values In addition: Warning messages: 1: In min(x) : no non-missing arguments to min; returning Inf 2: In max(x) : no non-missing arguments to max; returning -Inf 3: In min(x) : no non-missing arguments to min; returning Inf 4: In max(x) :

LLVMers, The 2.2 prerelease is now available for testing: http://llvm.org/prereleases/2.2/ If anyone can help test this release, I ask that you do the following: 1) Build llvm and llvm-gcc (or use a binary). You may build release (default) or debug. You may pick llvm-gcc-4.0, llvm-gcc-4.2, or both. 2) Run 'make check'. 3) In llvm-test, run 'make TEST=nightly report'. 4) When

Hi, I recently changed from uw imap to dovecot on the sound recommendation of a friend and have mostly succeeded in getting all of my clients up and running, but am really stuck with the iPhone which is failing to make connections. I run certificates on all of my clients and thunderbird happily connects both locally and remotely. I installed the certificate on the iPhone after great pain (pk12

[You can find an easier to read and more complete version of this RFC here <https://docs.google.com/document/d/1QidaJMJUyQdRrFKD66vE1_N55whe0coQ3h1GpFzz27M/edit?ts=5aaa84ee#> .] Knowing instruction scheduling properties (latency, uops) is the basis for all scheduling work done by LLVM. Unfortunately, vendors usually release only partial (and sometimes incorrect) information. Updating the

I tried multiple imputation with aregImpute() and fit.mult.impute() in Hmisc 3.8-3 (June 2010) and R-2.12.1. The warning message below suggests that summary(f) of fit.mult.impute() would only use the last imputed data set. Thus, the whole imputation process is ignored. "Not using a Design fitting function; summary(fit) will use standard errors, t, P from last imputation only. Use

Target: FreeBSD 7.0-RC1 on amd64. autoconf says: configure:2122: checking build system type configure:2140: result: x86_64-unknown-freebsd7.0 [...] configure:2721: gcc -v >&5 Using built-in specs. Target: amd64-undermydesk-freebsd Configured with: FreeBSD/amd64 system compiler Thread model: posix gcc version 4.2.1 20070719 [FreeBSD] [...] objdir != srcdir, for both llvm and gcc. Release

Hello, I'm new to R and have been following many guides including the two-way anova (http://www.personality-project.org/r/r.anova.html). Using that walkthrough including the supplied data I do str(data.ex2) and receive the appropriate types of data as follows: > str(data.ex2) 'data.frame': 16 obs. of 4 variables: $ Observation: int 1 2 3 4 5 6 7 8 9 10 ... $ Gender :