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 brevity.
On March 23, 2017 8:22:47 AM PDT, Paul Bernal <paulberna...@gmail.com> wrote: >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 the database, >the >following happens, for example: > >January-2000, Feb-2000, Apr-2000, Jun 2000 (I have missing >observations) > >when I am supposed to have the sequence January-2000, Feb-2000, >Mar-2000, >Apr-2000, May-2000, Jun-2000, etc. > >How can I model a time series when there are missing months? I was >planning >making up fictional or fake observations with a value of 1 to fill in >the >gaps but not sure if this is a reasonable approach. > >Any help and/or guidance will be greatly appreciated, > >Best regards, > >Paul > > [[alternative HTML version deleted]] > >______________________________________________ >R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide >http://www.R-project.org/posting-guide.html >and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
