Timeseries Analysis I have the weekly time series data from 2011 to 2014 with 6 variables (Gross_Revenue, Attendence, Enrollmentcount etc.) and its having seasonality. I want forecast the Gross_Revnue for 2015 1st 15 weeks by using timeseries model. Please suggest me for which I need to use for this data. Either multivariate model or any ARIMA model.
 A: From reading your question, I feel that you may need more background. This book is fabulous and it is so good I purchased it but you may read if for free.
Forecasting: principles and practice
https://www.otexts.org/fpp/8/3
All the code is in R and you can follow the examples and in one day, you'll be able to solve your problem.
A: As @nickcox says there are many times series models.  The family of forecasting models can be seen here http://www.autobox.com/cms/index.php/afs-university/intro-to-forecasting/doc_download/23-forcasting-family-tree where ARIMA models are a subset of Transfer Function Models (includes causal vbariables).  Some guidelines to developing a time series model  can be found here http://www.autobox.com/cms/index.php/blog/entry/build-or-make-your-own-arima-forecasting-model. If you have possible predictors then by all means you should be considering multivariate time series models : note that simple multivariate regression is a particular case of a Transfer Function. Finally I had a role to play with the development of AUTOBOX and you should investigate a number of software providers including the free ones.
