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It's great that Granger causality analysis has been incorporated in `mne_connectivity.spectral_connectivity_epochs`, which supports extensive **frequency-** and **time-frequency-domain** connectivit…
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Dear all,
I have two 500ms' length of MEG time series, along the time, directional information of correspond cortical fields will change dynamically. If I want to model this directional changing, how…
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I personally like the idea of sliced causality a lot. And I consider our branch model to be an instance of the sliced causality that only captures the control-flow part. I understand that the static a…
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**Notebooks & Github codes**
- [ ] [Quickstart Notebook for using Causalgraphicalmodels python module: used to describe and manipulate Causal Graphical Models and Structural Causal Models. ](https:…
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There is an issue on chapter 14, in the following paragraph
[paragraph here]
Another less obvious case when fixed effect fails is when you have reversed causality. For instance, let’s say that it is…
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what do you mean by Use multivariate analysis to understand the relationship between my two datasets ?
Do you mean a granger causality analysis ?
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Hello Anna,
do you know any good ressources (papers or websites) on Granger Causality? I'm curious about the analysis.
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Reproducible computational environments for research
- Virtual environments, docker, git
Neural data handling and preprocessing
- Spiking data
- LFP
- Calcium imaging
- Widefield imaging
Single c…
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The compiler just reports that a causality analysis occurred without giving information on the variables that generate this error.
This is a well-known weakness of constraint programming: it is hard …
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see discussion in https://groups.google.com/d/msg/pystatsmodels/WtqcXF3KtJI/wVH4HrHtHVMJ
target: get equivalent to Stata's `teffects`
## References
mix between statistics, econometrics and Stata (…