similar to: aggregate.ts (PR#514)

I'm having some problems with aggregate.ts, e.g. R> x <- ts(1:20) R> frequency(x) [1] 1 R> aggregate(x, nfreq=1/3) Error in aggregate.ts(x, nfreq = 1/3) : cannot change frequency from 1 to 0.333333333333333 In fact aggregate.ts only accepts a new frequency that is a negative power of two in this example. The problem with the current test for compatible frequencies if

This message is in MIME format --_=XFMail.1.3.p0.Linux:990702182137:16900=_ Content-Type: text/plain; charset=us-ascii 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

Consider the following scrap of code: > x<- ts(1:50,start=c(1,11),freq=12) > y <- aggregate(x,nfreq=4) > c(y) [1] 6 15 24 33 42 51 60 69 78 87 96 105 114 123 132 141 > y Error in rep.int("", start.pad) : invalid number of copies in rep.int() > tsp(y) [1] 1.833333 5.583333 4.000000 So we can aggregate into quarters, but we cannot print it using

Consider the following scrap of code: > x<- ts(1:50,start=c(1,11),freq=12) > y <- aggregate(x,nfreq=4) > c(y) [1] 6 15 24 33 42 51 60 69 78 87 96 105 114 123 132 141 > y Error in rep.int("", start.pad) : invalid number of copies in rep.int() > tsp(y) [1] 1.833333 5.583333 4.000000 So we can aggregate into quarters, but we cannot print it using

This message is in MIME format --_=XFMail.1.1.p0.Linux:970825095458:252=_ Content-Type: text/plain; charset=us-ascii 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 <-

I'm probably apporaching this all wrong to start but.... Suppose I have a monthly time series and I want to compute the mean of months 6,7, and 8. I want to plot the original time series and the seasonal time series, one above the other. When I do that as below the time series don't line up for reasons that are obvious. How can I change the base of the seasonal time series so I can make

>represented. They are now R "objects" similar to S-PLUS "rts" >time series, but they are 3-dimensional arrays (iterations x variables >x chains). This seems like the best choice of data structure to me >but if someone else has thought more deeply about this tell me now >before I rewrite all my code! Martyn A couple of years ago I wrote a kernel of routines

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

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) ##

Hi, I have a ts object with a frequency of 4, i.e., quarterly data, and I would like to calculate the mean for each quarter. So for example: > ts.data=ts(1:20,start=c(1984,2),frequency=4) > ts.data Qtr1 Qtr2 Qtr3 Qtr4 1984 1 2 3 1985 4 5 6 7 1986 8 9 10 11 1987 12 13 14 15 1988 16 17 18 19 1989 20 If I do this manually, the mean

>>>>> 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

I'm having trouble with column-subsetting a multivariate time series. The underlying problem is with start(). R> x <- ts(matrix(rnorm(100), ncol=2)) R> y <- aggregate(x, ndeltat=2) R> y[,1] Error in ts(y, start = start(x), freq = frequency(x)) : invalid start R> start(y) [1] 2 1 R> frequency(y) [1] 0.5 The point where the error occurs in ts() is:

I have done a re-working of the time series code in base R and library ts that will appear in Friday's snapshot. I am sure at least one person will be dissatisfied, but I am convinced there are fewer errors than there were before (I found more than 20, as well as several documented features that did not exist.) The principles in the code are: tsp attributes can only go on vectors of length

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

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

I have a suggestion for kernapply for ts objects. When we choose the option circular=F, the returned series don't have the correct dates. The removed dates are all at the beginning instead of half at the beginning and half at the end. It is particularly useful when we need to smooth the series (or remove a trend using a filter) before estimating a model (like in macroeconomics) or simply

Hello all, I use arima to fit the model with fit <- arima(y, order = c(1,0,1), xreg = list.indep, include.mean = TRUE) and would like to use predict() to forecast: chn.forecast <- rep(0,times=num.record) chn.forecast[1] <- y[1] for (j in 2:num.record){ indep <- c(aa=chn.forecast[j-1], list.indep[j,2:num.indep]) # this is the newxreg in the

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

This seems like a FAQ, but I can't figure it out. I have a mv ts object: R > tsp(pg) [1] 1982 2003 1 R > dim(pg) [1] 22 12 and a univariate ts: R > tsp(rw) [1] 1690 1996 1 Yet, when I try to intersect them: R > tsp(ts.intersect(rw, pg)) [1] 1982 2176 1 the process goes awry. How to I get rw and pg to be one ts that runs from 1982 to 1996 and has 13 univariate time

Time Series functions in R ========================== I think a good basic S-like functionality for library(ts) in base R would include ts class, tsp, is.ts, as.ts plot methods start end window frequency cycle deltat lag diff aggregate filter spectrum, spec.pgram, spec.taper, cumulative periodogram, spec.ar? ar -- at least univariate by Yule-Walker arima -- sim, filter, mle, diag, forecast