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I am running R 1.2.2 under Linux. When using the function stl in the ts library, how can I save the seasonal component? What I would like was something like: library(ts) data(nottem) data.stl <- stl(nottem, "per") x <- data.stl$sea This what I get: > x NULL I would, however, like to store in x the seasonal component. Thanks in advance. Francisco. -- Francisco

Hi all, How can the label of the x-axes in the plot() of a stl.object be adapted? e.g., When plotting: plot(stl(nottem, "per")) In the labels of the x-axes is “time”. How can this be changed to e.g., “Time (dekade) “? It does not work with xlab or others anymore… Thanks, Jan _______________________________________________________________________ Ir. Jan Verbesselt Research

Hi, I have a monthly time series with missing values and I would use stl function to identify seasonality. I tried all settings of na.action but the result is the same: stl(tm245,s.window=11, na.action=na.pass) Error in stl(tm245, s.window = 11, na.action = na.pass) : NA/NaN/Inf in foreign function call (arg 1) Can you help me? Thanks Andrea Toreti [[alternative HTML version

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

Hi, I'm dealing with time series. I usually use stl() to estimate trend, stagionality and residuals. I test for normality of residuals using shapiro.test(), but I can't test for autocorrelation and heteroskedasticity. Is there a way to perform Durbin-Watson test and Breusch-Pagan test (or other simalar tests) for time series? I find dwtest() and bptest() in the package lmtest, but it

Hi, This is actually a theory question. I'm a bit confused by the s.window parameter in the stl() function (which is in the ts package). For example, in the stl documentation it uses the nottem data, and then: plot(stl(nottem, s.win = 4, t.win = 50, t.jump = 1)) What does it mean by s.win = 4? Is it because a year has 4 seasons (namely Spring, Summer, Autumn and Winter)? If so will it

I don't understand the output of stl. As a simple example: y <- numeric(1:365) y[250] = 1 stl <- stl(ts(y, frequency=7), s.window="periodic") This returns without error but the results are puzzling to me. If you plot the results it is probably easiest to visualize what I mean. plot(stl) This shows the original data (a single spike at 250). A trend (which also shows a bump

I just realized after some tips and a little digging that what I was trying to do "manually" has already been done. I was trying to fit my data using 'lm' then taking the "residual" data and trying to do a spectral estimate (for seasonality) usiing fft and then passing the "residual" of all of that to arima to get the irregular portion of the time series

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi I would like to add a line to the plot of the data panel of a stl decomposed time series. Example: plot(stl(nottem, "per")) plots a 4(or is t 8?) panel graph. I thought that I might be able to use mfg to plot in the top (left?) panel ("data"), but it is not working. Any help appreciated, Rainer - -- Rainer M. Krug,

Coming from a C++ and C# background I would like to know how inheritance works with 'R'. The classical example is I can define an abstract class 'Shape' and have an array of 'Shape's but each instance could be a Circle, Square, Triangle, etc. because they all derive from 'Shape'. At runtime if I wish I can tell the type of the 'Shape' using various language

Hi, I'm trying to make a ts object that has both NA values and a frequency other than 1 (so I can use stl). I've tried all permutations I can think of, but cannot get the desired (expected?) results. The values live in x and the corresponding semi-regular time stamps are in t: > library('zoo') > z = zoo(x, order.by=t, frequency=24) > zzr = as.zooreg(z, start=0) > zr

I have a data set of monthly river flows from 1960-2000, which are similar in structure to the nottem data: > klam.flow Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep 1961 1461 1716 2524 1773 1906 2005 1756 1575 1387 983 1094 1382 1962 1907 2253 1985 1907 1769 1676 2634 1386 929 766 968 1309 ... I tried plotting with > ts.plot(klam.flow) Which quickly led me to

I am trying to understand the nuances of STL (seasonal trend decomposition with loess) based on William Cleveland's (and others?) original development. I do not understand the specification or use of "frequency components" or equivalent "low-pass filter" components in the stl() function. I have run the stl() function on a standard example data (co2) in both S-Plus and

G'day, I am looking at monthly reports, and have three series of monthly data from 2007 to 2009. I would like to show the season decomposition of these two series side by side on the one device, however using plot doesn't seem to respect any use of layout(matrix(1:3, ncol=3)) or par(mfcol=c(1,3)). I'm guessing that this means that the plot(stl) perhaps uses them, but I can't find

R Help Community I'm trying to understand time series (TS) objects. Thought I understood but recently have run into a series of error messages that I'm not sure how to handle. I have 15 years of quarterly data and I typically create a TS object via something like... data.ts <- ts(mydata, start = 2002, frequency = 4) this create a matric as opposed to a vector object as I receive a

Hello On Wed, 2008-01-23 at 00:10 +0300, Nikita Danilov wrote: > Hello, > > below is a tentative list of tasks into which WBC effort can be > sub-divided. I also provided a less exact list for the EPOCH component, > and an incomplete list for the STL component. > > WBC tasks are estimated in lines-of-code with the total of (9100 + 3000) > LOC, where LOC is a non-comment,

Hi everyone. I'm having some troubles with STL function to decompose some data. My issue is that I have monthly data from September 2005 up to August 2010 i. e. 60 observations. I define it in the following way: *u<-read.csv("C:/CELEBREX.csv",header = TRUE) u.ts<-ts(u, start=c(2005,9), frequency=12) * The issue is that when I try to use stl(u.ts, 'per') Then the

Hi, There is a discussion thread on llvm-commits list about a possibility of using custom memory allocators for STL to improve the performance and reduce the memory pressure of STL containers, e.g. std::set. I thought that this discussion may be interesting for a wider audience and therefore I re-post the messages on llvm-dev as well. It would be interesting to hear what others think about -

On 1/21/2013 12:35 AM, Chris Lattner wrote: > > I'm confused here. You're acting as though we don't use the STL. In fact, we do use std::string, std::vector, std::map etc when they are the right solution for the job. I'm trying to understand the reasoning behind the decisions made at the beginning of LLVM. My working assumption is that ADT didn't exist when LLVM

Dear helpeRs, Is it possible to change the shading colour of the range bars in the plot generated by plot.stl? By default they are grey, but I would prefer them white (I am preparing some graphics for a powerpoint presentation so I'm inverting all colours). As far as I can see plot.stl allows you to turn off the range bars, but nothing about the shading colour. I tried to look at the