Enrico Schumann-2 wrote
>
> I cannot reproduce this error. I get...
>
> > sessionInfo()
> *R version 2.15.1* (2012-06-22)
>
# Thank you for testing, Enrico (Italian? ),
# it seems an updating issue.
# I am trying to update everything possible to the latest
# version because of compatibility.
Cren wrote
>
> # trying to run the following example code
> # from 'RQuantLib' package...
>
# Obviously, run
require(RQuantLib)
# before executing the example :)
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# Hi all,
# trying to run the following example code
# from 'RQuantLib' package...
HullWhite <- list(term = 0.055, alpha = 0.03, sigma = 0.01,
gridIntervals = 40)
Price <- rep(as.double(100),24)
Type <- rep(as.character("C"), 24)
Date <- seq(as.Date("2006-09-15"), by = '3 months
Roger Koenker-3 wrote
>
> There are obviously a large variety of non-smooth problems;
> for CVAR problems, if by this you mean conditional value at
> risk portfolio problems, you can use modern interior point
> linear programming methods. Further details are here:
>
> http://www.econ.uiu
Hans W Borchers wrote
>
> The most robust solver for non-smooth functions I know of in R is
> Nelder-Mead
> in the 'dfoptim' package (that also allows for box constraints).
>
> First throw out the equality constraint by using c(w1, w1, 1-w1-w2) as
> input.
> This will enlarge the domain a bit,
onte Carlo
> # simulated scenarios in order to quantify the
> # credit loss according to empirical transition
> # matrix. Then I am afraid of every solver finding
> # local maxima (or minima) because of some
> # "jump" in Credit VaR surface function of
> # portfolio weights :
# Whoops! I have just seen there's a little mistake
# in the 'sharpe' function, because I had to use
# 'w' array instead of 'ead' in the cm.CVaR function!
# This does not change the main features of my,
# but you should be aware of it
---
# The function to be minimized
sharpe <- function(w) {
# Hi all,
# consider the following code (please, run it:
# it's fully working and requires just few minutes
# to finish):
require(CreditMetrics)
require(clusterGeneration)
install.packages("Rdonlp2", repos= c("http://R-Forge.R-project.org";,
getOption("repos")))
install.packages("Rsolnp2", repos=
# I've read that rollapply, and its wrapper apply.rolling()
# from PerformanceAnalytics package, do not work with multivariate
# time series neither their output can be a multivariate time series.
# Then I was wondering if any other function like those exists, or
# if I need to write my own functi
# Thank you, Michael: it works fine!
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__
R-help@r-project.org mailin
# One more question, Joshua: let instead of merging tickers
# I would like to put prices from an OHLC object
# in weekly format, then selecting just the close prices.
# What would be a code to do it?
# I guess:
data = new.env()
ticker.list <- c('SPY', 'TLT', 'GLD')
getSymbols(ticker.list, env = da
Joshua Ulrich wrote
>
> Load the data into an environment, then merge them using do.call():
>
> series.env <- new.env()
> getSymbols(ticker.list, src='FRED', env=series.env)
> series <- do.call(merge, as.list(series.env))
>
>
Thank you very much, Joshua: this works very well!
Thank you :)
-
Hi all,
I would need to put datas downloaded with quantmod into a matrix or a data
frame.
Suppose to start from here:
*require(quantmod)
ticker.list <- c('AAA', 'ALTSALES','AMBNS','AMBSL','BAA',
'EMRATIO',
'FEDFUNDS', 'GASPRICE', 'GS1', 'GS10', 'GS20', 'LNS141000
Hi all,
I was wondering why I get errors trying to solve this:
*simeq <- function(x) {
f <- numeric(length(x))
f[1] <- x[1] * dnorm((log(x[1]/D) + (r + x[2]^2/2) * T)/(x[2] * sqrt(T)))
- D * exp(-r * T) * dnorm((log(x[1]/D) + (r + x[2]^2/2) * T)/(x[2] *
sqrt(T)) - x[2] * sqrt(T))
f[2] <- dn
Rui Barradas wrote
>
> Hello,
>
> ?setdiff
> setdiff(one, two)
>
Thank you for your help, Rui.
But
*> setdiff(one,two)
[1] "ciao"*
Where's "bello"?
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Sent from the R hel
Hi all,
let I have two text string:
*one <- c("ciao","zio","caio","bello")
two <- c("caio","zio")*
I would like to obtain a new text string which is* one - two* like this one:
[1] "ciao" "bello"
because "caio" and "zio" elements have been subtracted from *one*.
What's the most efficient way t
Hi,
unless you're dealing with heteroskedastic datas, the command *cor(x)* will
be enough, where *x* is your data matrix; in this function you can easily
select the method which has to be used: Pearson's, Kendall's or Spearman's
correlation.
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Thank you, Michael :)
Michael Weylandt wrote
>
> If that doesn't nail it down, I'll need you to answer the questions I
> asked in my previous email.
Previously I made a mistake with *dput()*, this is the correct output:
> dput(X)
new("timeSeries"
, .Data = structure(c(124.3, 124.38, 124.67,
Michael Weylandt wrote
>
> Can you provide a reproducible example?
>
Of course, Michael.
Consider the following time series:
11/2/2011 14:30 123.53
11/2/2011 15:00 123.78
11/2/2011 15:30 124.24
11/2/2011 16:00 124.2
11/2/2011 16:30 124.07
11/2/2011 17:00 123.91
11/2/2011 17:30 123.44
11/2/20
t seems to sum for me...
>
> z <- zoo(1:50, seq.POSIXt(from = Sys.time(), by = "30 min", length.out =
> 50))
>
> aggregate(z, as.Date(time(z)), sum)
>
> Best,
> Michael
>
> On Tue, May 15, 2012 at 11:52 AM, Cren <oscar.soppelsa@> wrote:
>>
Hello,
I have a time series with intraday datas, sampled every 30'; I would need to
aggregate them in this way: summing up all datas within a day.
I tried to use *aggregate(...)* function to get my goal, but it aggregates
in wrong way (I did not understand how so far); what I need is like
*sum(.
Pascal Oettli-2 wrote
>
> Hello,
>
> Probably you should try:
>> update.packages(checkBuilt=TRUE)
>
>> install.packages('gogarch', dependencies=TRUE)
>
> Best Regards,
> Pascal
>
Dear Pascal Oettli-2,
thank you for your suggestment; I was not aware of that command and it will
be very useful
Ok, solved.
If anyone had the same problem, just install the last gogarch pacakge (vers.
0.7-1) and restart R + R Commander after the package installation.
When you've restarted it, the command *require(gogarch)* should load fastICA
package in the end and it will work ;)
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If I use gogarch_0.7-1 the command *require(gogarch)* returns the following
error: *Error in get(".packageName", where) : cannot allocate memoby block
of size 3.2 Gb*
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Sent fro
Hi all,
I've just downloaded and installed the latest R 32-bit version plus RExcel
and R Commander.
I'm having several problems in loading gogarch package:
The command *library(gogarch, pos=4)* returns *ERROR: package/namespace load
failed for 'gogarch'*
The command *require(gogarch)* returns *Er
Hi all :)
Before posting, I used the "search" function to find a solution, but I
wasn't lucky.
I'm using RExcel; I've read several examples which explain how to call in
RExcel an R function via =RApply(...) but I don't understand how may I
include in the function several numeric arguments.
Take
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