Re: [R] Handling nonexistent observations in R for time series analysis and forecasting

> On Mar 27, 2017, at 7:15 AM, Paul Bernal wrote: > > Dear friends, > > Hope you are all doing great. I am trying to model historical data on > transits, and the dates are in the following format: 1985-10-01 > 00:00:00.000 (this would be october, 1985). > The data comes from an SQL Server Datab

Re: [R] Handling nonexistent observations in R for time series analysis and forecasting

Ok Jeff. Thanks. Bert On Mar 27, 2017 9:56 AM, "Jeff Newmiller" wrote: > Actually, I think his question is about R because one answer that has been > mentioned is to use the merge function, but I haven't felt the urge to > create a reprex for him (see Posting Guide) and he keeps posting in HT

Re: [R] Handling nonexistent observations in R for time series analysis and forecasting

Actually, I think his question is about R because one answer that has been mentioned is to use the merge function, but I haven't felt the urge to create a reprex for him (see Posting Guide) and he keeps posting in HTML so it would have been corrupted even if he had. Someone else also pointed out

Re: [R] Handling nonexistent observations in R for time series analysis and forecasting

A statistics, not really an R programming question, so I believe OT here. But: 1. See the CRAN Time series task view for what's available: https://cran.r-project.org/web/views/TimeSeries.html 2. stats.stackexchange.com is a good site for statistical questions. Cheers, Bert Bert Gunter "The t

[R] Handling nonexistent observations in R for time series analysis and forecasting

Dear friends, Hope you are all doing great. I am trying to model historical data on transits, and the dates are in the following format: 1985-10-01 00:00:00.000 (this would be october, 1985). The data comes from an SQL Server Database and there are several missing observations. The problem is that