similar to: Graphics: Improving a Lattice plot - can it be done ?

I am working on a script that takes numeric performance indicators and runs them against a series of regressors (dummy regressors, yes\no stuff via 0 and 1, e.g. Was is Christmas this week 0=no, 1=yes). The script is as follows (Written as a function): -- Begin Script -- doEnv <- function(HOUR,ENVNAME,REPORTNAME) { library(RODBC) library(forecast) library("geneplotter")

Hello R-folks, I don't get the color of the legend in a lattice-plot right. I select a palette from RColorBrewer and use (with a col = mypalette argument) it in the barchart plot. The resulting graph shows the new palette in the graph, but uses the standard palette in the legend rectangles. Adding a col argument into auto.key uses the new palette with the legend text, but not in the

Hello R-folks, I don't get the color of the legend in a lattice-plot right. I select a palette from RColorBrewer and use it in the barchart plot. The resulting graph shows the new palette in the graph, but in the legend rectangles the standard palette is used. Adding a col argument into auto.key uses the new palette with the legend text, but not in the rectangle fill. What am I missing?

I'm using ssplot for drawing a map of Austria and colour the nine provinces regarding their share of employment. Now I wanted to add the figures in each province and failed miserably. Using the locator() and text() function caused the error message "invalid graphics state". I try to show you what I have done below, maybe you can find a general fault in my codes. I know that it's

Dear list users, I modeled the probability of occurrence of one species: "Cyperus dilatatus". I modeled the species using three different approaches: c("random","target","index") What I want to achieve is to make a plot of all prediction maps in a row with to conditional variables, that is, with the species and the approach I prepared a data.frame to try

Greetings, Version 0.1.4-0 of the ChainLadder package is available via CRAN and http://code.google.com/p/chainladder/ The ChainLadder package, which is focused on claims reserving methods typically carried out by property/casualty insurance actuaries, has recently been enhanced to implement the methods in David Clark's 2003 CAS (Casualty Actuarial Society) *Forum* paper "LDF

2012/10/31 Chandana De Silva <chandana at desilva.id.au> > You _can_ do NAT. > > Set up a different libvirt network on each machine, like this; > 10.128.80.65 will have a libvirt network 192.168.65.0/24 > 10.128.80.66 will have a libvirt network 192.168.66.0/24 > > Set up each of these networks as routed networks. > > Now set up routing/iptables rules on each

Hi all, This is to say hello to all of you as we are starting the project Ogg on a Chip for our master thesis. More information can be found at http://oggonachip.sourceforge.net/. Cut from the homepage: "The Ogg Vorbis Player (http://www.xiph.org/ogg/vorbis/index.html) shall be implemented in form of a system-on-a-chip by using hardware/software co-design techniques. A prototyping board

Hi, in order to understand the Ogg Vorbis decoding algorithm, do you recommend any document/book/www? I have read those on the web page but look for something more detailed.. Thank you very much, Pattara The best things in life are free. - B.G. DeSilva (1927) ---------------------------------------------------------------------- Ott Pattara Kiatisevi T L W G M.Sc. INFOTECH Student,

Arrrrr, I think I've found a bug in the behavior of the stats::cor function when NAs are present, but in case I'm missing something, could you look over this example and let me know what you think: > a = c(1,3,NA,1,2) > b = c(1,2,1,1,4) > cor(a,b,method="spearman", use="complete.obs") [1] 0.8164966 > cor(a,b,method="spearman",