Re: [R] Converting irregular time series data into ts object
Sorry there were some errors in my email. Use this instead. Assuming that they both cover the same period of time then if you are willing to throw away some points then consider using only these 256 elements from the 305 series round(seq(1, 305, length = 256)) ## [1] 1 2 3 5 That is use the 1st 2nd, 3rd, 5th, etc. point in each year from the 305 series. This aligns them by throwing away 305-256=49 points per year in the 305 series so that both series can be set up with a frequency of 256 points per year. On Wed, Feb 19, 2020 at 10:37 AM Gabor Grothendieck wrote: > > Assuming that they both cover the same period of time then > if you are willing to throw away some points then > consider using only these 256 elements from the 305 series > > round(seq(1, 305, length = 50)) > ## [1] 1 7 13 20 26 32 38 44 ...etc... > > That is use the 1st ,7th, 13th, etc. point in each year from the > 305 series. This aligns them by throwing away 305-256=49 > points per year in the 305 series so that both series can be > set up with a frequency of 256 points per year. > > > > On Wed, Feb 19, 2020 at 8:36 AM Upananda Pani wrote: > > > > Dear All, > > > > I want to convert irregular time series daily data in to ts objects. For > > some years I have 305 days data and some years I have 256 days. > > > > I need your suggestion regarding the same. > > > > I have read tutorial on the same but not able to find solutions. > > > > With regards, > > Upananda > > > > [[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. > > > > -- > Statistics & Software Consulting > GKX Group, GKX Associates Inc. > tel: 1-877-GKX-GROUP > email: ggrothendieck at gmail.com -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com __ 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.
Re: [R] Converting irregular time series data into ts object
Assuming that they both cover the same period of time then if you are willing to throw away some points then consider using only these 256 elements from the 305 series round(seq(1, 305, length = 50)) ## [1] 1 7 13 20 26 32 38 44 ...etc... That is use the 1st ,7th, 13th, etc. point in each year from the 305 series. This aligns them by throwing away 305-256=49 points per year in the 305 series so that both series can be set up with a frequency of 256 points per year. On Wed, Feb 19, 2020 at 8:36 AM Upananda Pani wrote: > > Dear All, > > I want to convert irregular time series daily data in to ts objects. For > some years I have 305 days data and some years I have 256 days. > > I need your suggestion regarding the same. > > I have read tutorial on the same but not able to find solutions. > > With regards, > Upananda > > [[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. -- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com __ 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.
Re: [R] Converting irregular time series data into ts object
You should read about statistical imputation and decide what approach is appropriate for your data. This mailing list is for questions about R, not about statistics. Once you know what algorithm you need to apply, look up R functions that implement that algorithm using Google or the CRAN Task Views. If you find yourself with some example code that doesn't work the way you think it should, that would be an appropriate time to first read the Posting Guide and then come back and post a question using plain text email setting rather than html format (so we don't receive a scrambled version of your broken example code). On February 19, 2020 5:35:29 AM PST, Upananda Pani wrote: >Dear All, > >I want to convert irregular time series daily data in to ts objects. >For >some years I have 305 days data and some years I have 256 days. > >I need your suggestion regarding the same. > >I have read tutorial on the same but not able to find solutions. > >With regards, >Upananda > > [[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. -- Sent from my phone. Please excuse my brevity. __ 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] Converting irregular time series data into ts object
Dear All, I want to convert irregular time series daily data in to ts objects. For some years I have 305 days data and some years I have 256 days. I need your suggestion regarding the same. I have read tutorial on the same but not able to find solutions. With regards, Upananda [[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.
