similar to: stl and NA

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 all, I would like to adjust the monthplot() of an stl() so that for a time-series with freq=12 (months): a) the curve on the panel for the k-th month graphs the seasonal values minus their monthly mean values b) add to the fig. the values of the k-th month of the seasonal + remainder, also minus their monthly mean values which corresponds to the 'seasonal diagnostic plot as described by

Dear list, R-core, The documentation of stats::stl explicitly refers to the paper by Cleveland[1] to explain the parameters. However, the description is confusing, with two descriptions seeming to refer to the same parameter in the paper. s.window: [...] the loess window for seasonal extraction, which should be odd and at least 7, according to Cleveland et al --> The phrase 'odd and at

Hi all, I have a time series that contains double seasonal components (48 and 336) and I would like to decompose the series into the following time series components (trend, seasonal component 1, seasonal component 2 and irregular component). As far as I know, the STL procedure for decomposing a series in R only allows one seasonal component, so I have tried decomposing the series twice. First,

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 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

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, Is there anybody who could explain a little bit the use of s.window and t.window in STL. If I decompose a series using the default values, I get a very irregular trends, but if I play with the options, I get less rare trends. If anybody can explain me the concepts behind these options I will appreciate a lot. I'm not a mathematician ;-) Thanks in advance Cheers, Antonio Antonio

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 <-

-----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,

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

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

Hi there, My name is Renan X. Cortes, student of Statistics, from south of Brazil, and I'd like to ask you a few questions about decomposition of time series. In R, when I fit the decomposition using the "stl" function, an object is returned when ask the summary of the fit, called STL.seasonal (%), STL.trend (%) and STL.remainder (%). Once the decomposition is additive,

Hola. Estoy empezando a ver temas de series temporales y me gustaría saber como obtener con R los IVES (índices de variación estacionales). Por el momento estoy viendo cosas muy simples, como descomponer una serie en tendencia y componente estacional, usando la función decompose y también la función stl. Por ejemplo # generamos 48 datos de una normal por ejemplo x <- rnorm(48) # creamos el

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

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

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

Currently I find that if I call stl() repeatedly I can use the weights array that is part of the stil output to detect outliers. I also find that if I repeatedly call stl() (replacing the outliers after each call) that the "remainder" portion of the stil output gets reduced. I am calling it like: for(.index in 1:4) { st <- stl(mt, s.window=frequency(mt), robust=TRUE)

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 doing analysis on hourly precipitation on a file that is disorganized. However, I managed to clean it up and store it in a dataframe (called CA1) which takes the form as followed: Station_ID Guage_Type Lat Long Date Time_Zone Time_Frame H0 H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 H22 H23 1