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**Is your feature request related to a problem? Please describe.**
Sktime does not have exponential smoothing predictor which is able to calculate confidence intervals.
**Describe the solution you…
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## Description
Probably this is not a bug. I'm trying to understand how `shuffle_models()` works based on [this](https://github.com/microsoft/LightGBM/issues/1815) and [this](https://github.com/m…
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Currently `lm`, `glm`, `MASS::glm.nb`, `brms::brm`
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Time series data can be naturally clamped at a limit - could be lower limit or upper limit.
Provide an option to the user to set this limit such that the predictions and intervals do not cross it.
…
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I want to construct Bootstrap Confidence Intervals for XGBoost regression using python. I developed my case based on codes (https://machinelearningmastery.com/calculate-bootstrap-confidence-intervals-…
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When render the book, time series doesen't goes on the line
## calculate confidence intervals and prediction intervals
observed
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Patrick Smela shared that success criterion drastically changes replication success rate - we should report that very clearly (in both annotator and explorer) so that users can report in a meaningful …
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- [x] prediction_intervals complete
- [x] allow the user to specify just one interval
- [x] only train up the intervals that users actually ask for
- [x] figure out return values (probably a datafr…
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Currently we simulate from the model using a parametric bootstrap. We showed in the GLM vignette that this is valid if the model is "true", and the simulation is still relatively fast, but a parametri…
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In #631 @sbfnk suggested adding an additional argument, `type = c("quantile", "interval") to `get_coverage()`.
Below is a full proposal for what the function could look like. One open question is …