I am running ARMA model on time series data. Data consists of price changes in S&P 500 during the day, recorded at 4 predefined time stamps( 8:30, 10:30,10:15, 3:12, hence non equidistant)
My question is, do I need to worry about the data being non equidistant? If so, how do I modify my series to account for it? Or is it safe to assume data as being equidistant,as it may not have a strong influence on the final forecast? Thanks! -Ritz -- View this message in context: http://r.789695.n4.nabble.com/Equidistant-time-spacing-of-time-series-data-tp3960790p3960790.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list 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.
