There is also a package imputeTS, which may be able to do what you want.
It has a nice Introduction vignette and also appears to have nice plot
functions
Berend Hasselman
> On 24 Mar 2017, at 02:11, David Winsemius wrote:
>
> There's also an irts-package "irregular time series"
>
> Sent fr
There's also an irts-package "irregular time series"
Sent from my iPhone
> On Mar 23, 2017, at 3:42 PM, John C Frain wrote:
>
> Google "arima missing data r" will bring up several references including
> http://stats.stackexchange.com/questions/104565/how-to-use-auto-arima-to-impute-missing-val
Google "arima missing data r" will bring up several references including
http://stats.stackexchange.com/questions/104565/how-to-use-auto-arima-to-impute-missing-values.
There are several other useful results in that search.
John C Frain
3 Aranleigh Park
Rathfarnham
Dublin 14
Ireland
www.tcd.ie/Ec
Even the most basic introduction to R discusses the use of NA for missing data.
Injecting values that could be mistaken for actual readings is a dangerous
approach. You can use the merge function to introduce missing rows into zoo
objects or data frames.
--
Sent from my phone. Please excuse my
Dear all,
Hope you are doing well. I am trying to model the historical number of
transits of a particular market segment, but the problem is that I have
missing data.
I am working with monthly data, so I have 12 observations per year (in
general). The problem is that, when I bring the data from t
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