Fit an AutoRegressive Integrated Moving Average (ARIMA) model to predict values in the future.
> **Note:** This is depreciated. Forecasting - AutoRegressive Integrated Moving Average (ARIMA) API is an example built with Microsoft Azure Machine Learning that fits an ARIMA model to data input by the user and subsequently outputs forecasted values for future dates. Will the demand for a specific product increase this year? Can I predict my product sales for the Holidays season, so that I can effectively plan my inventory? Forecasting models are apt to address such questions. Given the past data, these models examine hidden trends and seasonality to predict future trends. *While this web service could be consumed by users � potentially through a mobile app, website, or even on a local computer for example, the purpose of the web service is also to serve as an example of how Azure ML can be used to create web services on top of R code. With just a few lines of R code and clicks of a button within the Azure ML Studio, an experiment can be created with R code and published as a web service. The web service can then be published to the Azure Marketplace and consumed by users and devices across the world with no infrastructure set-up by the author of the web service.*