Displaying 13 results from an estimated 13 matches for "0.0328".
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0.032
2005 Feb 04
2
no. at risk in survfit()
Hi,
when I generated a survfit() object, I can get number
of patients at risk at various time points by using
summary():
fit<-survfit(Surv(time,status)~class,data=mtdata)
summary(fit)
class=1
time n.risk n.event survival std.err lower 95% CI
upper 95% CI
9.9 78 1 0.987 0.0127 0.963 1
41.5 77 1 0.974 0.0179 0.940 1
54.0 76
2009 Feb 08
0
Initial values of the parameters of a garch-Model
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
2017 Oct 10
2
Expose aliasing information in getModRefInfo (or viceversa?)
Yes, this is odd.
On my clang.bc
Without:
2.2967 ( 53.8%) 0.0242 ( 26.4%) 2.3210 ( 53.2%) 2.3227 ( 53.2%)
Memory SSA
2.3364 ( 53.7%) 0.0246 ( 25.7%) 2.3610 ( 53.1%) 2.3636 ( 53.1%)
Memory SSA
2.3353 ( 54.0%) 0.0258 ( 27.0%) 2.3611 ( 53.4%) 2.3632 ( 53.3%)
Memory SSA
With two getModRefInfo calls:
3.0302 ( 58.8%) 0.0328 ( 29.9%) 3.0630 ( 58.2%) 3.0858 ( 58.2%)
2007 Feb 26
0
LD50 contrasts with lmer/lme4
Dear R-list,
I have a data set from 20 pigs, each of which is tested at crossed 9 doses
(logdose -4:4) and 3 skin treatment substances when exposed to a standard
polluted environment. So there are 27 patches on each pig. The response is
irritation=yes/no.
I want to determine "equally effective 50% doses" (similar to old LD50), and
to test the treatments against each other. I am looking
2005 Nov 18
2
(no subject)
Hi,
I need to run a Fisher's exact test on thousands of 2x2 contingency tables, and
repeat this process several thousand times (this is a part of the permutation
test for a genome-wide association study).
How can I run this process most efficiently? Is there any way to optimize R code?
I have my data in a 2x2xN array (N ~ 5 K; eventually N will be ~ 500 K), and use
apply inside the loop:
2002 Sep 11
1
lme with/without varPower - can I use AIC?
I want to compare the following two models in AIC
(Treat, Spotter are categorial, p is pressure, Pain is
continuous)
PainW.lme<-lme(Pain~p+Treat*Spotter,data=saw,random=~p|Pat,
weights=varPower(form=~Pain))
# AIC= -448
Pain.lme<-lme(Pain~p+Treat*Spotter,data=saw,random=~p|Pat)
#AIC = -19.7
Note the huge differences in AIC, and the estimated power of 6.
A plot of the residual
2002 Jun 19
2
split plot design with missing plots
Windows 2000 . 5.00.2195 with Service Pack 1.
R 1.5.1
Output from my split-split plot aov "alerted" me that I have done something
wrong. I designed an experiment with all combinations of all levels of each
treatment, but lost a little data (3 out of 192 plots). With the following
data, I run the following model:
> collim[c(1:6,187:192),c(1,3:6,9)]
plot Litter Fert
2017 Oct 09
2
Expose aliasing information in getModRefInfo (or viceversa?)
On Mon, Oct 9, 2017 at 1:57 PM, Daniel Berlin <dberlin at dberlin.org> wrote:
> FWIW: Bootstrap is probably not a good test of this, there are bugs filed
> where we end up with tons of loads and stores to test against each other.
> That's actually fairly rare in bootstrap, as you can see.
> Let me get you some test cases.
>
SG, thanks!
>
> My guess is that we
2017 Oct 10
2
Expose aliasing information in getModRefInfo (or viceversa?)
I'm trying to understand what is the result we'd seek in the example
in D38569 (pasting here for quick access)
double f(double a)
{
double b;
double c,d;
double (*fp) (double) __attribute__ ((const));
/* Partially redundant call */
if (a < 2.0)
{
fp = sin;
c = fp (a);
}
else
{
c = 1.0;
fp = cos;
}
d = fp (a);
2007 Sep 18
0
[LLVMdev] 2.1 Pre-Release Available (testers needed)
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
2008 Jan 28
0
[LLVMdev] 2.2 Prerelease available for testing
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
2008 Jan 24
6
[LLVMdev] 2.2 Prerelease available for testing
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
2007 Sep 15
22
[LLVMdev] 2.1 Pre-Release Available (testers needed)
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