search for: 0.0212

Hi, I have a transition matrix T for which I want to find the steady state matrix for. This could be approximated by taking T^n , for large n. T= [ 0.8797 0.0382 0.0527 0.0008 0.0212 0.8002 0.0041 0.0143 0.0981 0.0273 0.8802 0.0527 0.0010 0.1343 0.0630 0.9322] According to a text book I have T^200 should have reached the steady state L L

Building the current release 2.7 branch on x86_64-apple-darwin10 with r81455 reverted, I get the following Polyhedron 2005 benchmark results (with no test failures)... ================================================================================ Date & Time : 7 Apr 2010 22:24:16 Test Name : llvm_gfortran_lin_p4 Compile Command : llvm-gfortran -ffast-math -funroll-loops -msse3

This should be very easy, but alas, I'm very new to R. My end goal is to calculate p-values from arima(). Let's say I just ran this: > MyModel <- arima(y[1:58], order=c(1,0,0), xreg=MyData[1:58,7:14], > method="ML") > MyModel And I see: arima(x = y[1:58], order = c(1, 0, 0), xreg = MyData[1:58, 7:14], method = "ML") Coefficients: ar1

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

On Apr 7, 2010, at 8:41 PM, Jack Howarth wrote: > Building the current release 2.7 branch on x86_64-apple-darwin10 > with r81455 reverted, I get the following Polyhedron 2005 benchmark > results (with no test failures)... Very nice! A 14% speedup on a benchmark we don't tune for isn't bad. I imagine that there are several easy wins you could get on it if you were interested

On Wed, Apr 07, 2010 at 09:54:36PM -0700, Chris Lattner wrote: > > On Apr 7, 2010, at 8:41 PM, Jack Howarth wrote: > > > Building the current release 2.7 branch on x86_64-apple-darwin10 > > with r81455 reverted, I get the following Polyhedron 2005 benchmark > > results (with no test failures)... > > Very nice! A 14% speedup on a benchmark we don't tune for

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

[CCing Dale since this was his change, not mine] The change in 81455 fixes a compiler crash. It doesn't happen very often, but I can't imagine we would want to back that out. Fixing it would be a more reasonable solution. From a quick look at it, the problem is that gcc/config/darwin-c.c is registering va_opt for GC. When you build for Fortran, darwin-c.o is not linked so the GC gets

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

On Thu, Apr 08, 2010 at 08:45:48AM -0700, Bob Wilson wrote: > [CCing Dale since this was his change, not mine] > > The change in 81455 fixes a compiler crash. It doesn't happen very often, but I can't imagine we would want to back that out. Fixing it would be a more reasonable solution. From a quick look at it, the problem is that gcc/config/darwin-c.c is registering va_opt

On Apr 8, 2010, at 8:45 AMPDT, Bob Wilson wrote: > [CCing Dale since this was his change, not mine] > > The change in 81455 fixes a compiler crash. It doesn't happen very often, but I can't imagine we would want to back that out. Fixing it would be a more reasonable solution. From a quick look at it, the problem is that gcc/config/darwin-c.c is registering va_opt for GC.

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",

On Fri, Sep 14, 2007 at 11:42:18PM -0700, Tanya Lattner wrote: > The 2.1 pre-release (version 1) is available for testing: > http://llvm.org/prereleases/2.1/version1/ > > [...] > > 2) Download llvm-2.1, llvm-test-2.1, and the llvm-gcc4.0 source. > Compile everything. Run "make check" and the full llvm-test suite > (make TEST=nightly report). > > Send

LLVMers, The 2.1 pre-release (version 1) is available for testing: http://llvm.org/prereleases/2.1/version1/ I'm looking for members of the LLVM community to test the 2.1 release. There are 2 ways you can help: 1) Download llvm-2.1, llvm-test-2.1, and the appropriate llvm-gcc4.0 binary. Run "make check" and the full llvm-test suite (make TEST=nightly report). 2) Download