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I am drawing two plots on the same graphics device window as follows: yLim<-range(range(template),range(slope*subSeries) ) plot( template, type="p", pch=19,cex=1.75,lwd=2.5,lty=1, ann=F, axes=F,frame.plot=T,col="red", ylim=yLim,new=T ) title( main = "myDotChart of original template and subSeries vs time" );points( slope*subSeries, type="p", pch=15,cex=1.35,lty=2,lwd=2.5, c...

...g to Cleveland et al --> The phrase 'odd and at least 7' refers to Cleveland's parameter n_(s), section 3.5 of [1]. Confusing: Cleveland calls this 'seasonal smoothing', not extraction. l.window: the span (in lags) of the loess window of the low-pass filter used for each subseries.[...] --> The description 'low-pass filter used for each subseries' also seems to correspond to Cleveland's parameter n_(s), in step two of the algorithm in the reference. (section 2.2 of [1]). Confusing: Cleveland does not apply a low-pass filter to each subseries[2]. The subser...

Just by re-examining my question I found the answer ! segments(3, template[3], 3,slope*subSeries[3], col= "orange",lwd=2)I corrected the subSeries Points as they appear on the graph withslope*subSeries[3].thank youLloyd L [[alternative HTML version deleted]]

Hi, I want to apply a function (in my case SDF; package ?sapa?) repeatedly over discrete sections of a daily time series object by sliding a time window of constant length (e.g. 10 consecutive years or 1825 days) over the entire ts at increments of 1 time unit (e.g. 1 year or 365 days). So for example, the first SDF would be calculated for the daily values of my variable recorded between years 1

Can someone enlighten me on why the following doesn't work? setwd('C:/Temp/R') d <- rep(1:53,2) (s <- ts(d, frequency=53, start=c(2000,10))) n <- length(s) k <- n%/%3 for(i in (n-k):n) { st <- c(start(s)[1] + (start(s)[2] + i)%/%frequency(s), (start(s)[2] + i) %% frequency(s)) ed <- c(start(s)[1] +

Hi R-Helpers, I'm dealing with the STL procedure and trying to apply the tsdiag and StructTS onto the ts object to analyse the different parameters which need to be set. How can I use the tsStructure & tsdiag to create a seasonal, trend and cycle subseries plot so that I can select & analyse the correct np,ns, nt and nl? The problem is that too much signal goes into the seasonal variation and that the trend is not followed as it should. I tried already several values for all the parameters following the article guidelines of Cleveland but the...

Hello, I would like to implement a "turn-of-the-month' trading strategy in R. Given a daily series of stock market return data as a zoo object, the strategy would go long (buy) four trading days before the end of the month, and sell the third trading day of the following month. How can I select these days, particularly the fourth day before and the third day after the turn of the

...scussion 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 here). If you really do want to take a subseries from a regular time series, a modified version of window.ts would do. I am attaching my suggested modifications. Martyn On 02-Jul-99 maechler@stat.math.ethz.ch wrote: > >>>>>> On Fri, 02 Jul 1999, Adrian Trapletti <Adrian.Trapletti@wu-wien.ac.at> >>>>>...

The following seems confused (0.65 snapshot) > x <- ts(1:20) > window(x, 1, 1) Time Series: Start = c(1, 1) End = c(1, 1) Frequency = 1 [1] 1 Warning message: Not returning a time series object in: [.ts(x, i) (it of class ts, as the print method shows). Under 0.64.2 it is even more confusing: > x <- ts(1:20) > window(x, 1, 1) Warning: Not returning a time series object

>>>>> 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

Hello R helpers, I'm trying to use Mahalanobis distance to calculate distance of two time series, to make some comparations with euclidean distance, DTW, etc, but I'm having some dificults. I have, for example, two objects: s.1 <- c( 5.6324702, 1.3994353, -3.2572327, -3.8311846, -1.2248719, 0.9894694, -2.2835332, -5.1969285, -5.2823988, -3.1499400, -1.7307950, 2.8221209,

Dear list, I have a dataset containing values obtained from two different instruments (x and y). I want to generate 5 samples from normal distribution for each instrument based on their means and standard deviations. The problem is values from both instruments are non-negative, so if using rnorm I would get some negative values. Is there any options to determine the lower bound of normal

I'm looking for a histogram variant in which data points are plotted as labelled rectangles 'piled up' to form a histogram. I've posted an example at https://www.dropbox.com/s/ozi8bhdn5kqaufm/labelled_histogram.png?dl=0 It seems to have a long pedigree, as I see it (as in this example) in documents going back beyond the '80s. But I've not seen it in recent textbooks. So it