similar to: how to change bar colours in plot.stl

helpeRs, I have a nice looking mosaic plot in an article to be published soon. Sadly, the published version will be in black and white and so ruin the advantage of the default shading scheme of tiles. What would readers suggest as an alternative shading scheme? If I have a black-and-white shading scheme graduated according to suitable cutoffs I won't be able to tell positive from

Dear guRus, I'm having trouble producing a levelplot with relative cuts for each panel (my data has large differences in scales, so I want to use quantiles for each panel). My attempts to change the 'at' argument in panel.levelplot function have not met with success. Below is a toy example. xy <- expand.grid(x = 1:3, y = 1:3) aaa <- rbind(cbind(xy, z = 1:9, site =

Dear all, I'm trying to get a series of lattice levelplots to appear in viewports in a particular way but struggling to exert fine control over their appearence. There are two conditions: (a) I only want the levelplot to appear (I don't want axes, colour key, etc) in the viewport and (b) I want the levelplot to expand to the maximum allowable space in the viewport while observing

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

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, 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

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

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

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

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 All, I am in the process of writing an R extension in c++ and am using several STL containers (e.g., vector<double>, map<int, double>, multimap<int, double>). I make sure to clear all these containers at the end of the .Call. Everything compiles and runs just fine, but I'm a bit worried since I haven't found any other packages that use STL. So, my question: is it

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

I need to investigate how rollmean and the trend returned from stl differ. I am trying to find out exactly what the trend part of stl is (I have just started coding in R and do not know fortran). I need to extract this because it will be used in further calculations, and it needs to be verified to make sure that I am using the right process. I would like to use this to remove the seasonal

Greetings: I'm using the time series decomposition routine "stl" from the package "stats". But how do I get the results into a vector to work with them? example: data(AirPassengers) m<-stl(AirPassengers,"per") print(m) This lists the output but can't figure out how to extract the individual series like seasonal, trend, irregular. Thanks, Bob

Dear R Helpers, Currently I'm working with the ts package of R and created a TimeSerie from pixels extracted from satellite imagery(S10 NDVI data, 10 daily composites). I'm trying to decompose this signal in different signals (seasonal and trend). When testing out the STL method is says => Only univariate timeseries are allowed, but the current Timeserie I'm using is univariate!

Hi all, I am trying to analyse a time series data and want to make trend-season decomposition using STL approach in R. However I found the decomposition result seems to be sensitive to data points even with the robust option. More specifically, suppose I have a few years of monthly data. Using stl, I got a decomposition T1 + S1 + R1. Then I deleted the most recent two or three data points, the

Hi all, I'm working on decomposition and comparison of several time series. I'm interested in extracting the trend components for each time series using the stl function and overlaying them on one another. I'm not sure how to plot the trend function alone and to do the overlay using some kind of loop. If anyone has any insight that would be great! thanks, Katie -- View this

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 -

Hi mailinglist members, I’m actually working on a time series prediction and my current approach is to decompose the series first into a trend, a seasonal component and a remainder. Therefore I’m using the stl() function. But I’m wondering how to get the single components in order to predict the particular fitted series’. This code snippet illustrates my problem: series <-

Hi, I'm astudent in hydrobiology and I actually work on river's discharge and try to extract from my data the seasonal and trend components. I use STL function but I have several problems in understanding what this function have done. I'd like to know what means the IQR results which gave me some % about the seasonal component, trend component and the remainder component.