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There are a number of issues open for forecasting reducers (from forecasting to supervised regression and TSR), we should refactor and upgrade them.
All reducers (descendants of `_Reducer`) should …
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contributors: @fkiraly, @lynnssi, @mloning
## Purpose of the user guide
In addition to our API reference, we want to create a user guide. The API reference serves as a technical software reference…
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getting started with a wishlist for outlier robust multivariate location and scatter estimators
#3220 size (overall scaling)
- MCD in scikit-learn, not good with high contamination and large k_vars
-…
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### Description
Add multivariate analysis of covariance (MANCOVA)
### Purpose
To explore the relationship between multiple dependent variables, and one or more categorical and/or continuous explana…
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Python version 3.8.0
Tensorflow version 2.5.0
Tensorflow-probability version 0.13.0
Histogram of sampled data probabilites for n=2
![gp_2_points_data_hist](https://user-images.githubusercontent.co…
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Some tests are performed with Monte Carlo estimates. For example, in `test/matrix.jl` the `rand` function for the `Wishart` and `InverseWishart` distributions are tested by generating a lot of sample…
nfoti updated
3 weeks ago
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(Part of review [here](https://github.com/openjournals/joss-reviews/issues/6962).)
This was fun to read *and* I learnt some things :)
Some minor statistical/editorial comments on the paper:
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dill updated
2 months ago
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I'm trying to fit ngboost.distns.MultivariateNormal to 2D data (to predict covariance).
Unfortunately at the moment I am getting an error:
`AssertionError: MultivariateNormal is not useable for r…
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a good thing to add to manyglm would be observation weights (like the weights argument on glm).
Notes from David:
* These could be a vector (applied across rows of data) or a matrix (different wei…
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I would be happy to give an entire workshop on how to do meta-analyses with R as part of ESMARConf2022, covering the following topics:
- computation of effect size / outcomes,
- equal- and random-…