> 0.05 0.02 0.06
>
>> system.time(for(i in 1:1000) rowSums(cbind(mag, station)))
> user system elapsed
> 0.09 0.00 0.10
>
> See ?system.time, ?Rprof and http://code.google.com/p/rbenchmark/
> for timing commands.
>
> On Sat, Sep 26, 2009 at 11:16 AM, tzygmun
/FAQ/R-FAQ.html#How-do-I-convert-factors-to-numeric_003f
>
> If the problem were more basic, and you did not know what was in that
> dataset then the answer might have bee:
>
> str(attenu)
>
> --
> David
>
>
>
>
> On Sep 27, 2009, at 7:47 AM, tzygmu
reproducible code) that 'mag' was
> a matrix. If 'station' is a matrix, then
>
> mag + rowSums(station)
>
> will work. If that does not work, then you need to tell us what your
> data objects are.
>
> On Sat, Sep 26, 2009 at 11:39 AM, tzygmund mcfarla
(mag, station))
#
Thanks
On Sat, Sep 26, 2009 at 4:30 PM, jim holtman wrote:
> Probably more efficient if you remove the 'cbind' which would create a
> combined matrix. Use the following:
>
> rowSums(mag) + rowSums(station)
>
> On Sat, Sep 26, 2009 at 11:
Hi,
For very large matrices, is this the most efficient way to add two
variables together?
#
attach(attenu)
new<-rowSums(cbind(mag, station))
#
Also, could I be directed to some resources for working with very
large datasets?
Thanks
_
x', 1:3, sep="")
> # New suggestion
> sapply( Names, function( y ) list( get( y ) ) )
> Best,
> Jorge
>
> On Sat, Sep 19, 2009 at 6:51 PM, tzygmund mcfarlane <> wrote:
>>
>> Jorge,
>>
>> Your suggestions produce the names of the matrice
Ah, apologies. In the backing and forthing, I assigned the names to
the matrices. All sorted. Thanks!
On Sat, Sep 19, 2009 at 11:55 PM, Duncan Murdoch wrote:
> On 19/09/2009 6:51 PM, tzygmund mcfarlane wrote:
>>
>> Jorge,
>>
>> Your suggestions produce the names
;-paste("Table", i, sep="")
> print(get(disp))
> }
> # Suggestion 2
> disp <- paste("Table", 1:10, sep="")
> sapply(disp, function(x) print( get(x) ) )
> See ?print and ?get for more information.
> HTH,
> Jorge
>
> On Sat, Sep 19
Hi,
I am unable to do something fairly simple. I have matrices called
Table1,..., Table10. I want to be able to print them using a loop. So
I wrote:
##
for (i in 1:10){
disp<-paste("Table", i, sep="")
eval(parse(text=disp))
}
##
but this produces no output. Any
A quick question about stableFit() in the fBasics package. Is it
possible to constrain the gamma and delta parameters and only estimate
the alpha and beta parameters? I tried:
##
set.seed(1953)
r = rstable(n = 1000, alpha = 1.9, beta = 0.3)
stableFit(r, gamma=1, delta=0, type=c("q"
Hi,
I would like to compute a goodness-of-fit statistic for one data
series against a t-distribution, and obtain the quantiles of the
distribution of the statistic with given degrees of freedom. I wonder
if this is implemented in a package.
I know that the critical values have to be computed for
You got the order of the arguments wrong:
##
library(systemfit)
eqDemand <- consump ~ price + income
eqSupply <- consump ~ price + farmPrice + trend
fitsur <- systemfit(list(demand=eqDemand, supply=eqSupply), "SUR", data=Kmenta)
summary(fitsur)
##
Hi,
Does anyone know of a package/script that will implement the Whittle
(1953) estimator for the parameters of an invertible stationary ARMA
time series model? The estimator is defined on, for example, pg. 378
of Brockwell & Davis (1991).
I assume that the internal call .whittle in this code due
Hi,
I was wondering if there was an R package or routines for the Dantzig
Selector (Candes & Tao, 2007). I know Emmanuel Candes has Matlab
routines to do this but I was wondering if someone had ported those to
R.
Thanks,
T
---Reference---
@article{candes2007dantzig,
title={{The Dantzig selec
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