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![image](https://user-images.githubusercontent.com/17681226/92356173-3b065000-f118-11ea-8953-e4595f1de7b6.png)
This slide implies that code written for `Shape[]` will work for when it's substituted…
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R inline package might be a good place to start
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**Description of the issue**
This is meant to discuss how to properly compute the covariance matrix:
- is it correct to take into account the sky coverage correction, i.e. f_{sky}=12.25/5000 to …
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Hi all,
I'm considering using this module for data fitting with various functions (mostly Gaussian), however I can't find any references on how to generate/get the covariance matrix in order to extra…
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To help with parameter identification and estimation due to the high number of potential parameters, should we include estimated or fixed penalties on the covariance parameters?
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Hi there,
I am currently using multiple OAK-d cameras on a mobile robot for pedestrian detection. I have used the Spatial Tiny-yolo example as a template and then publish detections on a ros topic …
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### Describe the workflow you want to enable
Currently, Scikit-learn's LinearDiscriminantAnalysis (LDA) classifier does not support incremental learning through the partial_fit method. This poses c…
wcscr updated
1 month ago
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I would like to be able to run a GEE analysis using an unstructured covariance. In R this is very easy to do, e.g:
```
library(geepack)
geeglm(
outcome ~ . -cluster_id,
id = cluster_id,
…
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Just wanted to park your gist here since I came across it this week, looking for similar. I don't know if it's something we want to include or if it belongs in scipy or scikit-learn (I don't think it'…
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Hello, apologies if there's something I overlooked, but I am trying to figure out the easiest way to compute the voxel covariance matrix for an ROI based on the residuals from the GLM (useful for e.g.…