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related
#8274
#8269
#8261
I don't actually want normality tests, I want information about skew and kurtosis. (e.g. inference for variance depends on 4th moment but not on other features of a dis…
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**Feature Request: LangGraph Integration for Adaptive Agent Workflows in PufferLib**
**Objective**: Expand PufferLib’s capabilities by integrating LangChain, TRL (Transformers Reinforcement Learnin…
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General item that touches the fact of being assisted by a cloud platform.
# Experimentations
* A HuggingFace Space with Notebook to create musical inferences in the creative process of song/notes wr…
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## Papers we should implement
## SVARs
- [x] [Antolín-Díaz & Rubio-Ramírez (2018, AER)](https://doi.org/10.1257/aer.20161852) - narrative sign restrictions
- [x] [Arias, Rubio-Ramírez & Waggone…
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Are there any other segmentation model architectures or frameworks that we should consider using for this project?
Ideally we should be able to get these implemented and running in as close to native…
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Inferring a GIG from real data is probably going to be the most difficult part of the entire GIG project. This issue is to collect ideas and references.
For a start, I've just come across the paper…
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# - When is complete case analysis unbiased?
I have been thinking about scenarios under which it makes sense to use imputation for prediction models and am struggling to come up with a case. Yikes! E…
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I don't know where to put hypothesis tests and confidence intervals for variance and standard deviation.
It should have the usual test_, confint_, tost_, power functions for one and two sample cases …
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see summary issue #2041 and partially related #2050
score test with cluster robust standard errors. And by analogy other sandwiches will/should follow the same pattern
Guo, X., Pan, W., Connett, J.…
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We can estimate the variance based on the difference between observations y_i - y_j if they have the same mean, or we can remove the effect of a changing mean.
examples:
- robust variance estim…