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Add ITS scikit version plot to README.
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README.md

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@@ -178,7 +178,7 @@ Interrupted time series analysis is appropriate when you have a time series of o
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| Frequentist | Bayesian |
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| coming soon | ![](https://raw.githubusercontent.com/pymc-labs/CausalPy/main/docs/source/_static/interrupted_time_series_pymc.svg) |
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| ![](https://raw.githubusercontent.com/pymc-labs/CausalPy/main/docs/source/_static/interrupted_time_series_skl.svg) | ![](https://raw.githubusercontent.com/pymc-labs/CausalPy/main/docs/source/_static/interrupted_time_series_pymc.svg) |
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> The data, pre-treatment model fit, and counterfactual are plotted (top). The causal impact is shown as a blue shaded region. The Bayesian analysis shows shaded Bayesian credible regions of the model fit and counterfactual. Also shown is the causal impact (middle) and cumulative causal impact (bottom).
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docs/source/notebooks/generate_plots.ipynb

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