Requirement to Fit Input Data about copulae HOT 2 CLOSED

Hello,

1. To the first question, we use ranking. The basic idea is to order the data from 1...N and then divide by N. See the code snippets
   • pseudo_obs
   • rank_data
2. If I understand this question correctly, it wouldn't. Assume you had a data that you drew from some distribution and you did the integral transform (convert it to between 0 and 1), then it's result will be roughly the same.
   • You can try the following (pseudo-code here!):
     1. Generate some random variables. norm.random(n=1000)
     2. Get the cdf (integral transform) of it norm.cdf(rvs)
     3. assert cdf == psuedo_obs(rvs)
3. Not all copula classes converts the inputs to pseudo-obs. I believe empirical copulas don't. See Issue 21. The other copulae should convert data to pseudo-obs when they receive it because it generally doesn't hurt (from experience, most researchers forget to pass in the integral transform as inputs and just put in the raw data) and doesn't cost too much computation (done only once).
   • The general principle is that I try my best to choose sane defaults and abstract certain data transformations so researchers can have less stuff to consider in their head. It's possible to tweak any settings you'd like.

Hope this addresses your questions

from copulae.

Yes, that is helpful thanks! I may have another question or two as I continue to test this package, but this leaves me in a good spot right now.

from copulae.