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Hello, I’m a student majoring in biology in Japan.
I usually use Python so I'm very new to Julia...
I am trying to fit my experimental data(~400,000 angles, -pi ~ +pi bimodal) with mixture of von mises distribution.
I want to predict the parameters(mu, kappa, weights) and the number of components.
mydata
# Dict{Symbol,Any} with 1 entry:
:angle => ....
What I want is a posterior distribution of kappa, mu, and weights.
From the previous post : Incompatible Initial Value?, it looks like I'm specifying a wrong dimension to those parameters.
However, I can't figure out which code I must fix...
Any suggestions are welcomed.
I'm sorry for very basic qustion.
Thank you in advance.
sosuts
changed the title
Sample from mixture of VonMises distribution.(Incompatible Initial Value??)
Sample from mixture of VonMises distribution.(Ungiven Float64)
Nov 21, 2019
Sorry for the late response. This appears to be a problem with Distributions package (the VonMises distribution) and parameter checking. I will look into it today and file a pull request if I can fix it.
Hello, I’m a student majoring in biology in Japan.
I usually use Python so I'm very new to Julia...
I am trying to fit my experimental data(~400,000 angles, -pi ~ +pi bimodal) with mixture of von mises distribution.
I want to predict the parameters(mu, kappa, weights) and the number of components.
Below is the model I want to describe.
What I want is a posterior distribution of kappa, mu, and weights.
From the previous post : Incompatible Initial Value?, it looks like I'm specifying a wrong dimension to those parameters.
However, I can't figure out which code I must fix...
Any suggestions are welcomed.
I'm sorry for very basic qustion.
Thank you in advance.
The following is my code.
returns
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