Timeline for Forecast time series data with external variables
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| May 18, 2016 at 14:03 | comment | added | Tom Reilly | There also might be a Regression assumes that time isn't important. Regression was used by Galton to study Sweat Peas...not a time series problem. The Transfer Function uses parts of the process to estimate the problem. | |
| May 18, 2016 at 14:03 | comment | added | Tom Reilly | A Transfer Function model is explained in the Box-Jenkins textbook in Chapter 10. The goal is to build a model for each causal(pre-whitening) and then use the residuals to find correlations against Y(cross correlation). This will help you identify which variables are important and if there is any lead or lag relationships. There might be a need for ARIMA in this equation or denominator on the X variables. You might also have outliers, changes in trend, level, seasonality, parameters and variance. | |
| May 18, 2016 at 12:36 | comment | added | S.B | Hi sir, can you tell me more about a transfer function model? And why should I never use regression with time series data? Most studies suggest using regressing with time series. | |
| May 17, 2016 at 15:16 | comment | added | Tom Reilly | Never use regression with time series data. Use a Transfer Function model approach. | |
| May 17, 2016 at 7:48 | answer | added | Stephan Kolassa | timeline score: 14 | |
| May 17, 2016 at 7:16 | history | edited | mpiktas | CC BY-SA 3.0 |
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| May 17, 2016 at 2:15 | answer | added | Ezra Boyd | timeline score: 3 | |
| May 16, 2016 at 20:52 | history | edited | S.B | CC BY-SA 3.0 |
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| May 16, 2016 at 20:47 | answer | added | user78229 | timeline score: 3 | |
| May 16, 2016 at 20:36 | history | asked | S.B | CC BY-SA 3.0 |