Hi,
Does anyone know how to simulate a long time series (say 1000 daily series)
or generally a series, with inverse empirical distribution and generalized
pareto distribution (meaning to say the time series has a marginal
distribution of empirical and GPD distribution.) using the R package?
Does
Hi,
Does anyone know how to simulate a long time series (say 1000 daily series)
or generally a series, with inverse empirical distribution and generalized
pareto distribution (meaning to say the time series has a marginal
distribution of empirical and GPD distribution.) using the R package?
Does
Hi,
Does anyone know how to simulate a long time series (say 1000 daily series)
or generally a series, with inverse empirical distribution and generalized
pareto distribution (meaning to say the time series has a marginal
distribution of empirical and GPD distribution.) using the R package?
Does
Hi,
Does anyone know how to simulate a long time series (say 1000 daily series)
or generally a series, with inverse empirical distribution and generalized
pareto distribution (meaning to say the time series has a marginal
distribution of empirical and GPD distribution.)?
Does anybody know if ther
Hi,
I would like to know what is the easiest way to compile two or more set of
vectors or data frame, according to their index. They are interrelated to
one another by their assigned index. for example:
#data set 1
abc
#output:
X403 X408 X410 X415 X418 X419 X420 X423 X424 X425
Thanks a lot!
best
On Thu, Nov 1, 2012 at 8:19 AM, D. Rizopoulos wrote:
> try this:
>
> l <- list(c(1,2,3,7), c(3,4,5,6,3), c(4,2,5,7), c(2,4,6,3,2), c(3,5,7,2))
>
> sapply(l, head, 4)
>
>
> I hope it helps.
>
> Best,
> Dimitris
>
>
> On 11/1/2012 9
Hi,
I have this lame question. I want to convert a list (each with varies in
length) to matrix with same row length by eliminating vectors outside the
needed range.
For example:
l<-list(NULL)
l[[1]]=1,2,3.7
l[[2]]=3,4,5,6,3
l[[3]]=4,2,5,7
l[[4]]=2,4,6,3,2
l[[5]]=3,5,7,2
#so say I want to only h
Hi,
I got a small problem on how to define the vector index without manually
inspect the vector.
example:
y=c(2,3,5,2,4,6,8,3,6,2,5) #I have ten set of this kind of vectors (with
different values but same length) that I would also like to run the routine
below
#say;
v=the first index in y where
Hi,
I'm trying to compile two functions into one function. the first funtion is
called 'fs' which is self-made function, another function is from the
built-in 'integration' function that is copy-paste-edited. If built
separatey, these functions work well. However that is not the case if
combines t
Many Thanks :)
On Wed, Aug 8, 2012 at 2:43 PM, J. R. M. Hosking wrote:
> On 2012-08-08 04:22, Al Ehan wrote:
>
>> Hi,
>>
>> I have been having difficulties in finding packages/ codes that simplify
>> plotting of a GEV fitted to dataset (by L-moments) that would
Hi,
I have been having difficulties in finding packages/ codes that simplify
plotting of a GEV fitted to dataset (by L-moments) that would print out
graph comprising dataset versus gumbel reduced variate n return period at
the same. Anyone can help me on this? Thanks.
[[alternative HTML v
Hi guys,
I'm trying to use the the integral function to estimate the area under a
PDF and a crossing curve. first I stated the function with several vectors
in it:
fn=function(a,b,F,mu,alpha,xi)
{
x<-vector()
fs<-function(x)
{
c <- (mu+(alpha*(1-(1-F)^xi)/xi))
tmp <- (1 + (xi * (x - mu))/alpha)
>
> I hope it helps.
>
> Best,
> Dimitris
>
>
>
> On 6/27/2012 1:31 PM, Al Ehan wrote:
>
>> Hi R-users,
>>
>> I'm trying to repeat the same procedure to 1000 data set. I know this is
>> very easy, but I got stuck finding the right and fastes
se, you could use something like
> the following:
>
> estIID50 <- lapply(IID50, function (m) pargev(lmom.ub(m)))
>
> I hope it helps.
>
> Best,
> Dimitris
>
>
>
> On 6/27/2012 1:31 PM, Al Ehan wrote:
>
>> Hi R-users,
>>
>> I'm trying to
Hi R-users,
I'm trying to repeat the same procedure to 1000 data set. I know this is
very easy, but I got stuck finding the right and fastest way in running it.
IID50=Riidf[1:50,1:1000] #where IID50 is a dataframe consist of 1000 time
series(as column) and 50 time scales (row).
#what I tried to
I'm so very happy to receive your email. I've been stuck so long trying to
figure out just why! silly me. Thanks a bunch!
On Wed, Jun 20, 2012 at 11:50 AM, Peter Ehlers wrote:
> On 2012-06-19 23:33, Al Ehan wrote:
>
>> Hi guys,
>>
>> I'm trying to use
Thanks!
On Sun, Jun 17, 2012 at 1:18 AM, Miguel Manese wrote:
> Hi Al, Michael,
>
> On Sat, Jun 16, 2012 at 11:01 AM, R. Michael Weylandt
> wrote:
> > On Fri, Jun 15, 2012 at 6:56 AM, Al Ehan wrote:
> >> Hi,
> >>
> >> I would like to make
Hi guys,
I'm trying to use lmomco package. first I did the manual calculation on
what is the estimates scale and location parameter given L-CV=0.2, L1=1000
L-moments and k (shape parameter) =- 0.1. so what i get is:
location: 821.0445
scale:260.7590
shape:-0.1000
#I assign this as GEV ve
Hi,
I would like to make a replication of 10 of a linear, first order
Autoregressive function, with respect to the replication of its innovation,
e. for example:
#where e is a random variables of innovation (from GEV distribution-that
explains the rgev)
#by using the arima.sim model from TSA pack
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