Hi,
Which package/function do you recommend for Granger causality between x
and y with an error correction term?
In my problem, economic theory maintains that x~ I(1); y~I(1), x-y ~I(0)
\begin{eqnarray}
\Delta x_t = g_0 + \lambda_{x}(x_{t-1}-y_{t-1})+\sum_{k=1}^{n}g_{1k}\Delta
x_{t-s}+\sum
I have over 8000 time series that I need to analyze and forecast. Running 1500
takes over 2 hours using just ETS, let alone Holt-Winters and ARIMA. So I am
looking at ways in shrinking the time to generate a 2 year forecast.
The code I am using successfully to run through the time series sequent
Hello,
Maybe functions "xts", "endpoints" and "period.apply" of the "xts"
package might help you.
Regards,
Pascal
On Fri, Feb 28, 2014 at 1:32 AM, Yang Yang wrote:
> Hi
>
> Currently I am working on a river discharge data analysis. I have the daily
> discharge record from 1935 to now. I want t
Hi
Currently I am working on a river discharge data analysis. I have the daily
discharge record from 1935 to now. I want to extract the annual maximum
discharge for each hydrolocial year (*start from 01/11 to next year 31/10*).
However, I found that the hydroTSM package can only deal with the natu
Awesome, exactly what I was hoping for! Thanks so much! You are right - I
put in the wrong end dates for the second day.
Best,
Kai
On Thu, May 9, 2013 at 4:01 PM, Rui Barradas wrote:
> Hello,
>
> Maybe the following will do it. Note, however, that in your data, for
> start day 2012-02-11,
Hello,
Maybe the following will do it. Note, however, that in your data, for
start day 2012-02-11, the end day is always 2012-02-12 so the time
differences will be negative.
fun2 <- function(x){
d <- numeric(nrow(x) - 1)
for(i in seq_len(nrow(x))[-1]){
start
Hi Rui,
thanks for the quick fix. I am still wrapping my mind around your
expression, but unfortunately it doesn't quite give me what I want. You are
calculating differences between the start times. However, I would like to
know the 'idle' periods between the events, ie the time between the end of
Hello,
If I understand it well, try the following.
tmp <- lapply(tapply(as.POSIXct(paste(df[,1], df[,2])), df[,1], diff),
`*`, 60)
lapply(tmp, as.integer)
Hope this helps,
Rui Barradas
Em 09-05-2013 11:45, Kai Mx escreveu:
Hi everybody,
I have an analysis problem that seems a little over
Hi everybody,
I have an analysis problem that seems a little overwhelming to me, but is
probably not too hard to solve for you guys. I have a (fairly large)
dataframe that indicates usage of a resource on different days:
df <-data.frame (
dstartday =c(rep('2012-02-10', 4), rep('2012-02-11', 5)),
-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Ista Zahn
Sent: 18 October 2012 16:43
To: vas
Cc: r-help@r-project.org
Subject: Re: [R] Time Series Analysis and Forecasting
Sure:
http://cran.r-project.org/web/views/TimeSeries.html
Next time please try google first.
Best,
Ista
O
Sure:
http://cran.r-project.org/web/views/TimeSeries.html
Next time please try google first.
Best,
Ista
On Thu, Oct 18, 2012 at 11:29 AM, vas wrote:
> Hello,
>
> I am totally new in the field of time series analysis and forecasting and R.
>
> I read that R is a powerful tool for time series. C
Hello,
I am totally new in the field of time series analysis and forecasting and R.
I read that R is a powerful tool for time series. Could anyone give me
navigation what models of time series are availiable in R etc?
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Hi folks,
i have some problems with my evaluation. We have collect tons of data from
23 testpersons for our new road study.
I have now a time series for each person and all the logs when he
accelerates or hits the break trying to solve five different tasks.
The dataset lools like:
#Unixtim
Hi
Slides of my talk on Time Series Analysis and Mining with R at
Canberra R Users Group on 18 July are available at
http://www.rdatamining.com/docs. It presents time series
decomposition, forecasting, clustering and classification with R code
examples.
Regards
--
Yanchang Zhao
PhD, Data Miner
E
> Date: Thu, 23 Jun 2011 15:41:25 -0700
> From: jmo...@student.canterbury.ac.nz
> To: r-help@r-project.org
> Subject: Re: [R] Time-series analysis with treatment effects - statistical
> approach
>
>
> Mike Marchywka wrote:
> >
> >> I discovered a
Mike Marchywka wrote:
>
>> I discovered a way to do repetitive tasks that can be concisely specified
>> using
>> something called a computer.
Now that's funny :)
There were not controlled tests. It was a field experiment testing the
effects that various pavement designs have on underlying soi
> From: rvarad...@jhmi.edu
> To: marchy...@hotmail.com; jmo...@student.canterbury.ac.nz;
> r-help@r-project.org
> Subject: RE: [R] Time-series analysis with treatment effects - statistical
> approach
> Date: Thu, 23 Jun 2011 02:59:19 +
>
> If you have any
rg [r-help-boun...@r-project.org] on behalf of
Mike Marchywka [marchy...@hotmail.com]
Sent: Wednesday, June 22, 2011 9:31 PM
To: jmo...@student.canterbury.ac.nz; r-help@r-project.org
Subject: Re: [R] Time-series analysis with treatment effects - statistical
approach
> Date: Wed, 22 Jun 2011 1
> Date: Wed, 22 Jun 2011 17:21:52 -0700
> From: jmo...@student.canterbury.ac.nz
> To: r-help@r-project.org
> Subject: Re: [R] Time-series analysis with treatment effects - statistical
> approach
>
> Hi Mike, here's a sample of my data so that you get an idea what I&
Hi Mike, here's a sample of my data so that you get an idea what I'm working
with.
http://r.789695.n4.nabble.com/file/n3618615/SampleDataSet.txt
SampleDataSet.txt
Also, I've uploaded an image showing a sample graph of daily soil moisture
by treatment. The legend shows IP, IP+, PP, PP+ which are
> Subject: [R] Time-series analysis with treatment effects - statistical
> approach
>
> Hello all R listers,
> I'm struggling to select an appropriate statistical method for my data set.
> I have collected soil moisture measurements every hour for 2 years. There
Hello all R listers,
I'm struggling to select an appropriate statistical method for my data set.
I have collected soil moisture measurements every hour for 2 years. There
are 75 sensors taking these automated measurements, spread evenly across 4
treatments and a control. I'm not interested in being
On Fri, Mar 4, 2011 at 12:33 PM, Paco Pastor wrote:
> Hi everyone
>
> I am trying to do some time series analysis with daily temperature data (40
> years). I have created a zoo object and ts object but can't apply stl
> function. It says the series is not periodic or has less than two periods.
> I
Hi everyone
I am trying to do some time series analysis with daily temperature data
(40 years). I have created a zoo object and ts object but can't apply
stl function. It says the series is not periodic or has less than two
periods. I've searched through google and found a lot of messages abou
pred", the
predictions, and "se", the estimated standard errors" as time series
when se.fit = TRUE.
See also:
predict.Arima {stats}
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David W
standard errors" as time series
when se.fit = TRUE.
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--
David Winsemius, MD
West Hartford, CT
__
R-help@r-project.org mailing lis
For each arima model, can you output an associated confidence interval for
the predicted value at each time point?
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2. I create a new model with the same parameters, using "fixed" (check arima
documentation) on the new data
3. go to step 2. every time you have new data
It worked for me.
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S
You also may want to look at auto.arima in the 'forecast' package,
which will return the "best" ARIMA model based on AIC/AICc/BIC values
?auto.arima
hth
c
On 09/05/2010 06:02 PM, Stephan Kolassa wrote:
Hi,
basically, you know 5 periods later. If you use a good error measure,
that is.
I a
Hi,
basically, you know 5 periods later. If you use a good error measure,
that is.
I am a big believer in AIC for model selection. I believe that arima()
also gives you the AIC of a fitted model, or try AIC(arima1).
Other ideas include keeping a holdout sample or some such.
I'd recommend l
?
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https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do
I want to also choose the post optimal parameters in the order argument. How
could I easily do this?
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1. try the predict function
e.g. predict(arima1, n.ahead=10)
2. try the resid function
e.g. resid(arima1)
HTH
Pete
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quot;,")
attach(data)
training = data[1:120, 6]
test = data[121:245, 6]
ts1 = ts(training)
ts2 = ts(test)
arima1 = arima(ts1)
arima2 = arima(ts2)
[/CODE]
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Sent from the R help mai
How do I get the predicted values and the errors for each arima model?
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On Fri, 8 Jan 2010, Erin Hestir wrote:
I am trying to conduct a time series analysis on historic hydrologic data,
but I cannot coerce it into class ts because it does not have regular
sampling intervals (some years have 20 samples, other have 8). Specifically
I am trying to perform a CUSUM or or
The zoo package supports irregularly spaced time series and if your
create a zoo object z from your data then tt <- as.ts(z) will give you
a ts object, tt. Since a ts object must be regularly spaced this will
add NAs to ensure that it is.
On Fri, Jan 8, 2010 at 3:05 PM, Erin Hestir wrote:
> Hell
Hello,
I am trying to conduct a time series analysis on historic hydrologic data,
but I cannot coerce it into class ts because it does not have regular
sampling intervals (some years have 20 samples, other have 8). Specifically
I am trying to perform a CUSUM or or other step change detection, but
Dear R users
I am currently investigating time series analysis using an irregular time
series. Our study is looking at vegetation change in areas of alien vegetation
growth after clearing events. The irregular time series is sourced from Landsat
ETM+ data, over a six year period I have 38 scene
Hi, I am trying to analyze a time series with covariates. Since I have
basically no prior experience with time series modeling, I followed a
procedure suggested by Wooldridge, but I slightly changed the procedure and
wanted to ask whether it is sound or flawed in your opinion.
Wooldridge suggests
Hello, my name is Giusy and it's the first time I post in this forum. I'm a
beginner with R, I have to use it to analyse time series and I need some
help about these problems:
1. In my time series there are some NA values, but functions (arimaId,
arima,..) seem not to work in this case...what coul
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