Bump pcntoolkit from 0.35.0 to 1.1.2

[dependabot]

Bumps pcntoolkit from 0.35.0 to 1.1.2.

Release notes

Sourced from pcntoolkit's releases.

Version 1.1.2

Changes

1. Better default centile plot
2. Improve MSLL computation
3. Speedup model comparison
4. Change default Normal likelihood
5. Save predictions in normal order
6. Switch to SKLearn MAPE
7. Add centered random parameterization
8. Change default offset distribution to ZeroSumNormal

Bug fixes

1. Fix bug with re-submitting a runner's failed jobs
2. Fix bug with incremental file backup function
3. Solve problem that occurs when both n_batches and batch_size are specified
4. Small updates to default prior settings in HBR
5. Improve MSLL computation
6. Fix bug with nm.predict, it is now fully in-place on the Normdata
7. Fix transfer bug for HBR

Version 1.1.1

• Remove preprocessing before evaluation
• Don't recompute centiles in plotter

Version 1.1.0

Major changes

1. Add support for evaluate_logp for transfered BLR models

Bug fixes

1. Fix incorrect application of change-of-variables in BLR evaluate_logp
2. Correctly use semantic versioning
3. Correctly use the __version__ attribute

v1.0.1

Major changes:

1. NormativeModel.merge implemented, completing the federated learning arsenal
2. BLR transfer implemented
3. HBR model comparison using WAIC convenience function in util.model_comparison.py

Other nice things

1. Implemented ARD for BLR
2. Yhat estimation with importance weighting as default method
3. Fixed effect in the slope of mean and variance in BLR
4. Add vertical conditional density plots to plot_centiles function
5. Outlier detection and removal in NormData.from_dataframe
6. Model factory for common regression models

Minor changes:

... (truncated)

Commits

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