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Check and potentially implement a correlation-based distance. The distance metric may be better for calculating neighbors across space, time, and outcomes. Use the correlation distance outlined in MJ …
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It would be nice to export a function for the Kendall tau distance/bubble-sort distance as well as the Kendall tau correlation. In some situations it has a clearer interpretation.
https://en.wikipe…
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**Is your feature request related to a problem? Please describe.**
Metrics that require calculating pairwise distances between cells (e.g. distance correlation, co-ranking) currently can't be calcu…
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![screenshot 2016-09-06 13 46 12](https://cloud.githubusercontent.com/assets/6147456/18284532/50139bee-7438-11e6-8bde-e113df9431eb.png)
### Summary: For minimization, as the distance to the optima dec…
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Please excuse my ignorance if this is incorrect but I'm having a hard time using the CorrelationMatching class. It seems to me like this code below should normalize the distance[] array between 0 and…
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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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Dear all,
With energy library, I can easily calculate the distance correlation and the partial distance correlation.
I was wondering if it was possible to calculate the semi-partial distance cor…
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## Goal
We want to make a simulation study script that can be easily parallelizable.
## Context
For this simulation study we want to vary the number of central Rt curves for different situati…
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Our current implementation computed subject-wise correlation matrices, fisher's r2zs them, computes the euclidean mean and then inverts the fisher's r2z (i.e. z2r)
We could explore other distance f…
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Hello, thanks for making this code available! I'm working to replicate your distance notebook with some of our own data and in looking through the definition for the cross validated correlation I see …