Plotbounds for Turing

[orangebacked]

Is there any code to plot the bounds using Turing? I have succeeded in plotting the linear models but haven't been able to plot the quadratic or cubic models.

[goedman]

You mean using the plotbounds() method? Did you try converting the MCMCChains.Chains object to a DataFrame, e.g. DataFrame(chns, append_chains=true)?

If not, can you send me a MWE and I'll take a look. Clearly we're just starting creating a Turing version of StatisticalRethinking.jl.

[orangebacked]

Dear Mr. Goedman,

I was referring indeed to the plotbounds() method. I managed to plot it with the help of the Julia of the Julia community in Slack (you can find the discussion here https://stackoverflow.com/questions/62028147/plotting-credible-intervals-in-julia-from-turing-model/62070008?noredirect=1#comment109792812_62070008). This is the code (I hope it is useful):

weight_s = (d.weight .-mean(d.weight))./std(d.weight)
height = d.height
@model heightmodel(height, weight) = begin
    #priors
    α ~ Normal(178, 20)´
    σ ~ Uniform(0, 50)
    β1 ~ LogNormal(0, 1)
    β2 ~ Normal(0, 1)
    #model
    μ = α .+ weight .* β1 + weight.^2 .* β2
    # or μ = fheight.(weight, α, β1, β2) if we are defining fheigth anyways
    height ~ MvNormal(μ, σ)
end
chns = sample(heightmodel(height, weight_s), NUTS(), 10000)
describe(chns) |> display
res = DataFrame(chns)
fheight(weight, α, β1, β2) = α + weight * β1 + weight^2 * β2
testweights = -2:0.01:2
arr = [fheight.(w, res.α, res.β1, res.β2) for w in testweights]
m = [mean(v) for v in arr]
quantiles = [quantile(v, [0.1, 0.9]) for v in arr]
lower = [q[1] - m for (q, m) in zip(quantiles, m)]
upper = [q[2] - m for (q, m) in zip(quantiles, m)]
plot(testweights, m, ribbon = [lower, upper])

I'm transcribing the book with julia and Turing.jl, albeit slowly; let me know if I can colaborate! I saw this message today (I'm sorry for the delay), I guess I have to activate the notifications in my email.

Kind Regards, Emiliano Isaza V

[goedman]

Emiliano,

I apologize for not responding to your post. I don't understand how I missed your post 10 days ago, but somehow I must have deleted the notification.

I'll go over above code today and see where it differs from plotbounds() in SR and if it shows ways to improve plotbounds().

Best, Rob

[goedman]

Yes, very nice. I have started to use ribbons in other contexts as well but should probably rework this into plotbounds(). The other part I would like to allow in plotbounds() is to pass in a user defined link function like fweight() in your code above.

Have you looked at @karajan9 's work on TuringModels and SR? Looks really neat!