<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />Hi,
I have a continuous target variable Y- Brand Index- with data available for different points in time
The predictor variables I have are spends across different media channels over the same time period.
I would like to determine the BEST model to predict "Brand Index" basis the spends across channels
I would also like to understand the lift in Index contributed by each predictor variable
What kind of analysis should I do on JMP?
- Multiple Regression?
- Partitioning?
- Neural Networks?
How should I compare these models? ( since there is no Misclassification rate for continuous variables?)
Thanks
