Level: Advanced
Job Function: Analyst / Scientist / Engineer
Jian Cao, Principal Systems Engineer, JMP Division, SAS
Best Invited Paper Finalist
How to model and forecast the time series when it is interrupted due to interventions (e.g., process changes)? If you have leading indicators or other exogenous variables how can you incorporate them into your ARIMA models to make better forecast?
In this paper I will try to demystify the transfer function models in JMP with key use cases: Regression with ARIMA Errors, Distributed Lag Models and Intervention Models. I will demonstrate the benefits of using the transfer functions over the Ordinary Least Squares regression and ARIMA for building better forecasting models.
Presented At Discovery Summit Europe 2019
Presenter
Files
- Building Better Forecasting Models with Transfer Functions.pdf
- Building Better Forecasting Models.jrn
- Interventions Model Example.jmp
- Series M Sales and Leading Indicator for Forecast row 126-150.jmp
- Series M Sales and Leading Indicator row 1-125.jmp
- US Quarterly Growth Rates 1970Q1-2015Q4.jmp
- US Quarterly Growth Rates 2016Q1-2016Q3.jmp
- Building Better Forecasting Models PPT Slides 03.14.2019.pdf
