Displaying 20 results from an estimated 20000 matches similar to: "R-alpha: R documentation problems"
1999 Jul 02
0
Bug in "[.ts" for multivariate ts {Problem with plot.ts, "[" (PR#217)
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There was some discussion a while back on R-devel between Ross Ihaka,
Paul Gilbert and myself about row subsetting in time series. I think
the consensus was that "[.ts" should not try to coerce its result
back to a time series object (which is underlying the problem
2010 Apr 20
1
bug in aggregate.ts
Hi,
I am getting unexpected behaviour from aggregate.ts(). The 'ndeltat'
argument is effectively being reduced by 1 in some cases, even when it
is an integer, with the result that the blocks to be aggregated are
not of the expected size, and also that the end() of the aggregated
series is much later than the end() of the original series.
rawts <- ts(rep(1:10, each = 5), start = 1)
##
1997 Aug 25
0
R-alpha: ts problems
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Here is a patch which fixes some problems with time series functions.
Some examples of what goes wrong...
> x <- ts(rnorm(100),start=1,deltat=2)
> start(x)
Error in ts[1] : object is not subsettable
> end(x)
Error in ts[2] : object is not subsettable
> y <-
2011 Sep 23
1
Cross Spectrum : Conversion of 2-D spectrum into a single complex array
Hi, I'm wondering why the spectrum() phase of quadrature
couple isn't purely +/-pi.
But mostly, I'm looking for a recommended way to take a 2-D
spectrum and convert it into a single complex array.
Kindly consider:
# 10 Hz sine wave 10 seconds long sampled at 50 Hz
deltaT = 1/50
t = seq(0, 10, deltaT)
w = 2 * pi * 10
x = ts( sin( w * t ), deltat = deltaT )
y = ts( sin(
2006 Jul 13
1
ts and stl functions - still a problem
Hi
I am still having problems with using the stl function, when I read the csv file into R into a file called tkr and use dim(tkr) the result is 132 1 which is fine.
When coerce it into a trime series using ts either:
tstkr <- ts(t(tkr), deltat=1/12) or
tstkr <- ts(c(tkr), deltat=1/12)
and use the stl function I get the following error:
Error in
2008 Jul 08
2
time series by calendar week
hello,
i cant find a solution on this (might be) easy problem:
i have a time serie by carlandar weeks, so for every carlendar week i have a
value. now i would like to use the functions for time series, so i change
structur to a time serie with
cam <- ts(number,start=c(2001,1),deltat=7/365)
or
cam <- ts(number,start=c(2001,1),frequency=52)
the problem on it is, that 2004 had 53 calendar
2010 Apr 13
0
ccf problem (cross-correlation)
Hi all,
I have a problem concerning my understanding of the cross-correlation (ccf)
function in R.
assume a time serie as:
> t<-seq(0,6.28,by=0.01);
> my_serie<-ts(sin(t),start=0,end=6.28,deltat=0.01)
then I generate an other one shifted by 12 time points:
> my_shifted_serie<-ts(sin(t),start=0+0.12,end=6.28+0.12,deltat=0.01)
if I do the cross-correlation I get that the two
2012 Jan 07
1
using deltat parameter in time series in HoltWinters prediction
Hi.
I have to forecast a time series of a Internet network traffic bitrate.
The data are in file
http://www.forumaltavilla.it/joomla/datitesi/dati.datand the sampling
time is every 0.05 seconds.
Now, i want to use HoltWinters forecasting. This is my script.
dt=1.58443823e-9 #0.05 seconds in years
dati.ts=ts(scan("dati.dat"),start=0,deltat=dt)
model=HoltWinters(dati.ts)
1997 Oct 08
0
R-alpha: dump() / dput() -- fail for "environmental" and attributed functions
Here is a simple example to show what I mean:
f1 <- approxfun(1:3, 2:4)
dump("f1", file="")
which yields (in current development snapshot;
other versions are conceptually equivalent)
"f1" <-
function (v)
.C("approx", as.double(x), as.double(y), n, xout = as.double(v),
length(v), as.integer(method), as.double(yleft),
2006 Jul 12
1
ts and stl functions
Hi,
I have imported a csv file into R which contains one column (the rate er 100,000 population of a disease, by month over 11 years) I coerced into a time series using the following function,
tstkr<-ts(tkr,deltat=1/12)
This seems to work fine, and when I check for the class of the object using class(tstkr) I get "ts" as the response.
When I try to use the stl function in
2006 Jul 12
0
ts command and stl function
Hi,
I have imported a csv file into R which contains one column (the rate er
100,000 population of a disease, by month over 11 years) I coerced into
a time series using the following function,
tstkr<-ts(tkr,deltat=1/12)
This seems to work fine, and when I check for the class of the object
using class(tstkr) I get "ts" as the response.
When I try to use the stl function in stats
1999 Jul 27
3
Preliminary version of ts package
There is now a preliminary version of a time series package in the R-devel
snapshots, and we would welcome feedback on it. It is based in part on the
packages bats (Martyn Plummer) and tseries (Adrian Trapletti) and in part
on code I had or have written. (Thanks for the contributions, Martyn and
Adrian!) Some of the existing ts code has been changed, for example to plot
multiple time series, so
2011 Feb 16
2
leap years in temporal series command ts
Hi R community!
I'd like to create a temporal series with ts command for the interval
1st January 2002 - 31 December 2008. I have daily values, so this is a
2557 days temporal series. I'm using this command :
ts(observations, start=2002, end=2009, freq=365)
However, I don't get the correct temporal series since both frequency
(365 OR 366 for leap years) and deltat (1/365 OR
2008 May 16
0
wmtsa (wavCWT)
I can send data along, but it is too large for the list:
I am using wmtsa and the function wavCWT
I would like to use the range.scale to only evaluate a subset of
frequencies.
deltat of the time series that I am trying to analyze is 1
d = wavCWT(RM202.ts, range.scale = c(96, 2688))
and I get the error message
Error in wavCWT(RM202.ts, scale.range = c(96, 2688) :
Minimum scale must be greater
1999 Jul 02
1
Bug in "[.ts" for multivariate ts {Problem with plot.ts, "["} (PR#216)
>>>>> On Fri, 02 Jul 1999, Adrian Trapletti <Adrian.Trapletti@wu-wien.ac.at> said:
Adrian> There seems to be a problem with plot.ts (R Version 0.64.2)
> x<-cbind(1:10,2:11)
> x<-as.ts(x)
> plot(x)
Adrian> Error: subscript (20) out of bounds, should be at most 10
This is definitely a bug
--> CC: R-bugs
ALL NOTE : This is *not* new
2009 Feb 17
0
What's the predict procedure of ARIMA in R?
Hello,guys:
Recently, I am working on a seasonal ARIMA model. And I met some problem in the forecasting.
Now I just want to know that How does R perform the predict procedure(the predict formula, the initial setting of errors,etc.)?
I run the following commands and get the original code of the "predict" command, but I can't read it.
Can anybody explain it to me?
Thanks!
saji from
2003 Jul 29
1
OpenBSD-alpha and R-1.7.1 problem
I'm trying to get R running on OpenBSD/alpha.
I've applied some configure patches which I've previously sent to the
R-devel list to allow R to compile on an OpenBSD ELF platform (which
OpenBSD/alpha is, as the i386 port soon will be).
The patched source compiles without problems, and appears to run and
perform properly apart from two (possibly unrelated) problems.
1) On startup
2006 Mar 02
1
CCF and Lag questions
I am new to R and new to time series modeling.
I have a set of variables (var1, var2, var3, var4, var5) for which I have
historical yearly data.
I am trying to use this data to produce a prediction of var1, 3 years into
the future.
I have a few basic questions:
1) I am able to read in my data, and convert it to a time series format
using 'ts.'
data_ts <- ts(data, start = 1988, end =
2005 Aug 27
1
ARIMA (seasonal) backcasting & interpolation
Thanks for everyone's help with zoo -- I think I've got my data set
ready. (The data consists of surface weather temperatures, from 2002
to 2005, one observation per hour. Some values are missing... i.e. NA)
I have three goals:
GOAL #1:Get the data in proper time series form, preserving frequency
information:
> w4.ts <- as.ts( w3.zoo, frequency=(1/3600) )
I hope that 1/3600
2013 Feb 14
1
approxfun values
Readers,
According to the help '?approxfun', the function can be used to obtain
the interpolated values. The following test was tried:
> testinterpolation<-read.csv('test.csv',header=FALSE)
> testinterpolation
V1 V2
1 10 2
2 20 NA
3 30 5
4 40 7
5 50 NA
6 60 NA
7 70 2
8 80 6
9 90 9
10 100 NA
>