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This may be more of a discussion topic, but I post it here as perhaps discussions have not been activated yet in this repo, and it could be more appropriate to have this here rather than on the discourse.
I was wondering if there is a method to get a conditional distribution out of a ::BallTreeDensity.
So say for example that I have the following code:
using KernelDensityEstimate, Distributions
# define number of samplesconst n_samples =500# define two correlated variablesconst x =randn(n_samples)
const y = x.^2.+rand(Uniform(-0.0005, 0.0005), n_samples)
# and an uncorrelated oneconst z =rand(Gamma(), n_samples);
# fit the kde
kde =kde!(Array((hcat(x,y,z)')))
And I would like to get the distribution of x and y conditioned to, say, z = 10.
How would you do it?
Thank you very much
The text was updated successfully, but these errors were encountered:
Hello,
This may be more of a discussion topic, but I post it here as perhaps discussions have not been activated yet in this repo, and it could be more appropriate to have this here rather than on the discourse.
I was wondering if there is a method to get a conditional distribution out of a
::BallTreeDensity
.So say for example that I have the following code:
And I would like to get the distribution of
x
andy
conditioned to, say,z
= 10.How would you do it?
Thank you very much
The text was updated successfully, but these errors were encountered: