Dear R-people,
I tried to build a seasonal cycle sub-series plot of my time series using:
monthplot(nitrat.stl, choice="seasonal")
However, I only get the horizontal lines of the mean values and not the
vertical lines for each year. Can anybody help me?
Sincerely,
Anja
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On Tue, 2007-02-27 at 15:55 +0100, Anja Eggert wrote:
> I want to apply the stl-function to decompose a time series (daily
> measurements over 22 years) into seasonal component, trend and
> residuals. I was able to get the diagrams.
> However, I could not find out what are the equations behind it
I want to apply the stl-function to decompose a time series (daily
measurements over 22 years) into seasonal component, trend and
residuals. I was able to get the diagrams.
However, I could not find out what are the equations behind it. I.e. it
is probably not an additive or multiplicative combi
I'm not sure I understand what you want. However, I will suppose
I wanted essentially the same image as plot(stl..) but with individual
control over ylim for each of the 4 plots. In that case, I might make a
local copy of the actual plot function using 'getAnywhere("plot.stl")'
and modi
I am trying to plot the time series decomposition using plot(stl..).
Eventhough I understand why the scale of the 4 plots is better to be
unequal, I would like to plot all 4 in the same scale (otherwise
interpretation at a simple look may be misleading). Is there a way I could
do so (easier th
stl does this internally:
x <- na.action(as.ts(x))
so
stl(x, s.window, na.action = f)
is the same as
stl(f(as.ts(x)), s.window)
e.g.
nottem[25] <- NA # nottem is a built in data set in R
stl(nottem, "per") # error
stl(nottem, "per", na.action = na.contiguous)
lib
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 for
Hi,
maybe residuals are autocorreleted, you could you use
ARIMA models. See arima() in R to fit an ARIMA model.
Regards,
Vito
Sebastian.Leuzinger unibas.ch> wrote:
Hello, anyone got an idea on how to use stl() so that
the remainder eventually
becomes white noise? i used stl repeatedly but ther
Hello, anyone got an idea on how to use stl() so that the remainder eventually
becomes white noise? i used stl repeatedly but there is autocorrelation in
the remainder that i can't get rid of.
os: linux suse9.3
Sebastian Leuzinger
Institute of Bot
Pedro Rodrigues <[EMAIL PROTECTED]> wrote:
On Sun, 2004-07-18 at 18:38, bob mccall wrote:
> 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(
On Sun, 2004-07-18 at 18:38, bob mccall wrote:
> 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
bob mccall wrote:
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 extrac
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 s
Hi there,
Does anyone know whether missing value (NA) handling has been implemented in
the time series decomposition method stl. No matter what I do I cannot get
stl to accpet NAs.
I have looked in the archives and seen a similar posting
http://maths.newcastle.edu.au/~rking/R/help/03b/7092.htm
Hi,
I try to figure out what the stl-function exactly do.
I was reading the paper by Cleveland et al. (1990) and tested some features of stl
(the ability to decompose time series with missing values and the robustness feature).
I tried the following:
> data(co2)
> co2.na <- co2
> is.na(co2.na[c
On Wed, 30 Jul 2003, Jan Verbesselt wrote:
> 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 tr
Jan Verbesselt wrote:
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 met
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 u
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