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(I don't see an issue, but I thought it was mentioned before.)
Stata has accelerated failure time and proportional hazard parametric survival models. Implementing those is a GSOC idea that doesn't …
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### Describe the bug
The physical trough model will not progress in a reasonable time when conducting a parametric study on hours of storage and solar multiple with dispatch optimization enabled.
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There have been various questions about differences between results from DHARMa dispersion tests and other parametric overdispersion tests, such as [this](https://github.com/glmmTMB/glmmTMB/issues/224…
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### 🚀 Describe the improvement or the new tutorial
[`TorchSurv`](https://github.com/Novartis/torchsurv) is a Python package that serves as a companion tool to perform deep survival modeling within …
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The following functionality is being developed for future versions of **spm1d**:
**STATISTICS**
- P values for non-significant results
- Direction selection ("positive" or "negative") for one-tai…
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Scope of the paper is as follows:
- [x] #305
- [ ] #139
- [ ] #502
- [x] #306
- [ ] Writing document template of the article with all subsections
- [ ] Writing the paper, introduction, physica…
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**Mixture cure models** are used in survival analysis when not all subjects are expected to experience the event(s) under investigation. As reviewed in [Amico and Van Keilegom (2018)](https://www.annu…
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For the JPEG decoder example I expect we'll want some of the capability to play with numerical precision (i.e. quantization) and determine its impact on final result accuracy, since for the IDCT you c…
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- [x] Testing Eigen value solves
- [x] Testing Dynamic analysis
- [ ] Running comparison with 3D CAARC model with ParOptBeam
- [ ] Parametric study reevaluating results
- [ ] Writing results sec…
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Normal interval linear systems (that is the main functionality of this package currently) are quite useless. In most (prob. all) true applications, you have parametric interval linear systems (PILS, l…