search for: 0.0152

Hi I noticed a small inconsistency when using sum() vs cumsum() I have a char-based series > tryjpy$long [1] "0.0022" "-0.0002" "-0.0149" "-0.0023" "-0.0342" "-0.0245" "-0.0022" [8] "0.0003" "-0.0001" "-0.0004" "-0.0036" "-0.001" "-0.0011"

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

Hi all, I'd like to extract a value from an ANOVA table, but experience the following problem: ### This works: > s.pseudo <- summary(aov(m ~ block + mix*graz,data=split1)) > s.pseudo Df Sum Sq Mean Sq F value Pr(>F) block 2 1114.66 557.33 4.4296 0.04192 * mix 1 6.14 6.14 0.0488 0.82956 graz 2 1.45 0.72 0.0057 0.99427 mix:graz

Hello , I have estimated the following model, a sarima: p=9 d=1 q=2 P=0 D=1 Q=1 S=12 In R 2.12.2 Call: arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), optim.control = list(reltol = tol)) Coefficients: ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8 ar9 0.3152 0.8762 -0.4413 0.0152 0.1500 0.0001 -0.0413 -0.1811

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

Edward, you also can use the package aod on CRAN, see the help page of the function negbin. Best Matthieu An example: > library(aod) > data(dja) > negbin(y ~ group + offset(log(trisk)), ~group, dja, fixpar = list(4, 0)) Negative-binomial model ----------------------- negbin(formula = y ~ group + offset(log(trisk)), random = ~group, data = dja, fixpar = list(4, 0))

On Feb 19, 2011, at 11:25 AM, Jack Howarth wrote: > Is anyone able to bootstrap llvm-gcc42 svn on x86_64-apple-darwin10? Currently it is > failing here with... It was broken. I think I've fixed it in reverting 125960. -eric

>>>>> Tomas Kalibera >>>>> on Tue, 25 Aug 2020 09:29:05 +0200 writes: > On 8/23/20 5:02 PM, Rory Winston wrote: >> Hi >> >> I noticed a small inconsistency when using sum() vs cumsum() >> >> I have a char-based series >> >> > tryjpy$long >> >> [1]

On Mon, Feb 21, 2011 at 03:58:19PM -0800, Eric Christopher wrote: > > On Feb 19, 2011, at 11:25 AM, Jack Howarth wrote: > > > Is anyone able to bootstrap llvm-gcc42 svn on x86_64-apple-darwin10? Currently it is > > failing here with... > > It was broken. I think I've fixed it in reverting 125960. > > -eric Eric, The llvm-gcc42 bootstrap is fixed in

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

Comparing the Polyhedron 2005 benchmark results for gfortran from llvm-gcc-4.2 of April 7th, 2010 and September 18th, 2010 (from the rc2 2.8 release branch), we seem to be regressing in performance for this release.... ================================================================================ Date & Time : 7 Apr 2010 22:24:16 Test Name : llvm_gfortran_lin_p4 Compile Command :

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

Dear all, I have a data (bellow) and I want to make a correlation test with p-value structure(list(Name = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("CTJ", "PKR", "TTK"), class = "factor"), score = c(86.4371428571428, 89.7028571428572, 87.728, 89.99, 89.42, 85.6914285714286, 82.256,

[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

Is anyone able to bootstrap llvm-gcc42 svn on x86_64-apple-darwin10? Currently it is failing here with... /sw/src/fink.build/llvm-gcc42-2.9-0/llvm_gcc42_objdir/./prev-gcc/xgcc -B/sw/src/fink.build/llvm-gcc42-2.9-0/llvm_gcc42_objdir/./prev-gcc/ -B/sw/lib/llvm-gcc-4.2/x86_64-apple-darwin10/bin/ -c -g -O2 -mdynamic-no-pic -DIN_GCC -W -Wall -Wwrite-strings -Wstrict-prototypes -Wmissing-prototypes

Dear all I am working on unbalanced panel data and I can readily fit a "pooling" model using plm(), but not a "within" or "random" model. Reproducing the examples in vignette("plm") and in the AER package I encountered no such issues. ##unfortunately I cannot disclose the data, and it is too big anyway > dim(ibes.kld.exp.p[x.subs , ]) [1] 13189 34

Dear list, I'm currently trying to use the rms package to get predicted ordinal responses from a conditional ratio model. As you will see below, my model seems to fit well to the data, however, I'm having trouble getting predicted mean (or fitted) ordinal response values using the predict function. I have a feeling I'm missing something simple, however I haven't been able to

Hi there - I am using R1.5.1 on WinNT and the latest MASS (Venables and Ripley) library. Running the following code: >minimod<-glm(miniSF~gtbt*f.batch+log(mxjd),data=gtbt,family="binomial") >summary(minimod,cor=F) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.91561 0.32655 2.804 0.005049 ** gtbtgt 0.47171

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

Dear List, I am using both the clm() and clmm() functions from the R package 'ordinal'. I am fitting an ordinal dependent variable with 5 categories to 9 continuous predictors, all of which have been normalised (mean subtracted then divided by standard deviation), using a probit link function. From this global model I am generating a confidence set of 200 models using clm() and the