Does it make sense to build a regression model for time series data with breaks? Like the time series I posted below with one major break that mark the shift of time series feature?
Yes, of course it has. This task belongs to the section of regression analysis - regression with switchings (breaks). Your data can, for example, be approximated by a linear spline with unknown switching points.
What do you want to "see" in your data? Do you just want a smoot curve or do you want do discover a true pattern?
Yes, it is possible to develop regression models for time series data with breaks. Remember that this is also known as interrupted time series analysis, which uses regression techniques to model variations in the level or trend of a time series following an intervention or event. These models can be utilised to determine the impact of changes on a time series variable. It is essential, however, to ensure that the time series breaks are well-defined and supported by theory or empirical evidence. In addition, the validity of the regression models may be depending on the assumptions made regarding the nature and timing of the breaks as well as the potential confounding variables that may influence the outcome variable. Therefore, models require thorough consideration and validation to ensure accurate results.
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