Sent from my iPhone
> On Aug 31, 2024, at 10:55 AM, Christofer Bogaso
> wrote:
>
> Hi,
>
> I have run following code to obtain one step ahead confidence interval
> from am arima model
>
> library(forecast)
>
> set.seed(100)
>
> forecast(Arima(rnorm(100), order = c(1,0,1), xreg = rt(100,
В Sat, 31 Aug 2024 11:15:10 +
Stefano Sofia пишет:
> Evaluating the daily mean indipendently from the status is very easy:
>
> aggregate(mydf$hs, by=list(format(mydf$data_POSIX, "%Y"),
> format(mydf$data_POSIX, "%m"), format(mydf$data_POSIX, "%d")),
> my.mean)
>
>
> Things become more comp
Hi,
I have run following code to obtain one step ahead confidence interval
from am arima model
library(forecast)
set.seed(100)
forecast(Arima(rnorm(100), order = c(1,0,1), xreg = rt(100, 1)), h =
1, xreg = 10)
However this appear to provide the Prediction interval, however I
wanted to get the
Dear R-list users,
I deal with semi-hourly data from automatic meteorological stations.
They have to pass a manual validation; suppose that status = "C" stands for
correct and status = "D" for discarded.
Here a simple example with "Snow height" (HS):
mydf <- data.frame(data_POSIX=seq(as.POSIX
Stefano,
I see you already have an answer that works for you.
Sometimes you want to step back and see if some modification makes a problem
easier to solve.
I often simply switch to using tools in the tidyverse such as dplyr for parts
of the job albeit much of the same can be done using functio
Yes, very helpful.
Also, my second question was how can I extract the prediction standard error?
On Sun, Sep 1, 2024 at 1:00 AM Mark Leeds wrote:
>
> Chris: As David mentioned, if you have "new" data, then the interval has to
> be a prediction
> interval because the difference between a CI and
I want to obtain confidence interval for a new data as well as
estimate of SE for the new data
On Sat, Aug 31, 2024 at 11:58 PM David Winsemius wrote:
>
>
> Sent from my iPhone
>
> > On Aug 31, 2024, at 10:55 AM, Christofer Bogaso
> > wrote:
> >
> > Hi,
> >
> > I have run following code to obt
Chris: As David mentioned, if you have "new" data, then the interval has to
be a prediction
interval because the difference between a CI and a PI is that the PI is
constructed for data
that hasn't been seen yet. The CI is constructed for data that's already
there. I hope this helps.
On Sat, Aug 3
Thank you for all your suggestions.
Ivan's hint has been very easy to implement, a good solution indeed.
Thank you again
Stefano
(oo)
--oOO--( )--OOo--
Stefano Sofia PhD
Civil Protection - Marche Region - Italy
Meteo Section
Snow Section
Via del Co
Às 18:54 de 31/08/2024, Christofer Bogaso escreveu:
Hi,
I have run following code to obtain one step ahead confidence interval
from am arima model
library(forecast)
set.seed(100)
forecast(Arima(rnorm(100), order = c(1,0,1), xreg = rt(100, 1)), h =
1, xreg = 10)
However this appear to provide
Às 12:15 de 31/08/2024, Stefano Sofia escreveu:
Dear R-list users,
I deal with semi-hourly data from automatic meteorological stations.
They have to pass a manual validation; suppose that status = "C" stands for correct and
status = "D" for discarded.
Here a simple example with "Snow height"
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