Displaying 5 results from an estimated 5 matches for "algorithmus".
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algorithms
2013 Mar 28
1
make R program faster
...0.04 0.87 1.04 22.61
[<-.Date 0.04 0.87 0.18 3.91
vapply 0.04 0.87 0.14 3.04
%in% 0.02 0.43 0.18 3.91
+ 0.02 0.43 0.10 2.17
It comes from a simulation algorithmus that calculates day wise values
(values are depenend from the output of the day before). First I create
a data.frame with NAs. Finally each row contains the daily values.
output <- as.data.frame(matrix(nrow = 365, ncol = 50))
for (day in (1:365)) {
...
r <- list(Date=d,daylength=dayl...
2009 Sep 09
1
Package that does not work until I re write the exactly the same code
...))
Object["clusters"] <- clusterization(yLongData = as(Object,
"LongData"), xPartition = yPartition, convergenceTime =
resultKml[[2]],
imputationMethod = imputationMethod, startingCondition =
startingCond[iRedraw],
algorithmUsed = "kml")
assign(nameObject, Object, envir = parent.frame())
cat("*")
if (saveCld >= saveFreq) {
save(list = nameObject, file = paste(nameObject,
".Rdata", sep = ""))
sa...
2011 Nov 27
0
Need Help with my Code for complex GARCH (GJR)
...S, b4 = 1-S, dum = 1-S, alpha0 = 100*Var, alpha = 1-S,
beta = 1-S)
fitt<-maxLik(start=param, logLik=garch2,method="BHHH",
x=dat2$r_csi,Di=dat2$Di,Mi=dat2$Mi,Do=dat2$Do,Fr=dat2$Fr,y=dat2$r_t,z=dat2$r_sp,d=dat2$f)
Note that optim always breaks down:
nlminb and the BFGS and BHHH algorithmus from the maxLik-package work fine.
The estimated coefficients are similiar to those of the EVIEWS Estimation.
So I guess, they are correct.
Is my Implementation of the Dummy-Variabel in the VAriance-Equation
correct?
I failed to incorporate the GJR-term in the VAriance Equation. I tried to
modif...
2002 Apr 02
2
random forests for R
Hi all,
There is now a package available on CRAN that provides an R interface to Leo
Breiman's random forest classifier.
Basically, random forest does the following:
1. Select ntree, the number of trees to grow, and mtry, a number no larger
than number of variables.
2. For i = 1 to ntree:
3. Draw a bootstrap sample from the data. Call those not in the bootstrap
sample the
2002 Apr 02
2
random forests for R
Hi all,
There is now a package available on CRAN that provides an R interface to Leo
Breiman's random forest classifier.
Basically, random forest does the following:
1. Select ntree, the number of trees to grow, and mtry, a number no larger
than number of variables.
2. For i = 1 to ntree:
3. Draw a bootstrap sample from the data. Call those not in the bootstrap
sample the