On Wed, 1 Aug 2018 17:40:54 +0200 Edoardo Silvestri <silvestri.cas...@gmail.com> wrote:
> I have a database based on hourly data and I need to forecast next > 24h of a single variable. I was thinking about applying an ARIMA > model with some exogenous variables but I don't succeed to configure > the hourly frequency, estimate ARIMA parameters, pdq ( exists some > tests to check which parameters are better for the model?) and the > structure of the model in its easy form because I would also like to > introduce some seasonality form by analyzing some variables I > highlighted some daily and weekly behaviours similar. > > > > I recognize that it could be quite difficult the problem but if you > have also some useful links or some codes that can help me, please > send me. > You are talking about analyzing data in a regular time series. R has wide ranging time series analysis packages. I would suggest starting with the basic package that comes with an R download and reading the basic information associated with it. You could also checkout Venables and Ripley, _Modern Applied Statistics with S [which R is a dialect of]. If this is a homework question, hit the books. JWDougherty ______________________________________________ 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.
