Comments (3)
Your model doesn't make any random choices. Rather than sampling from a chain, the model is the chain. You need a ~
instead:
julia> m1 = @model begin
mc1 ~ Chain(Normal(0.0, 1.0)) do x Normal(x, 1.0) end
return mc1
end
@model begin
mc1 ~ Chain(Normal(0.0, 1.0)) do x
Normal(x, 1.0)
end
return mc1
end
julia> r1 = rand(m1())
Realized{Random._GLOBAL_RNG,UInt64,Chain{ggfunc-function,Normal{(:μ, :σ), Tuple{Float64, Float64}}}}(MeasureTheory.ResettableRNG{Random._GLOBAL_RNG, UInt64}(Random._GLOBAL_RNG(), 0x7f03d16a3be18246), Chain{ggfunc-function,Normal{(:μ, :σ), Tuple{Float64, Float64}}}(function = (x;) -> begin
(Main).Normal(x, 1.0)
end, Normal{(:μ, :σ), Tuple{Float64, Float64}}((μ = 0.0, σ = 1.0))))
julia> collect(take(r1, 10))
10-element Vector{Any}:
0.12741258475656037
1.6417485229031188
2.516541033750806
2.8617087554639085
4.121753061920916
5.781340260119851
4.174563930105311
4.485225714203611
4.696111390440044
5.622520863790941
from soss.jl.
Ah. Stupid mistake. Sorry for bothering and thank you for the answer!
Kind greetings!
from soss.jl.
No worries, hope you enjoy the package!
from soss.jl.
Related Issues (20)
- Examples page in documentation does not exist HOT 1
- sample(...) does not work HOT 9
- No more Soss.predict() methods for densities from Distributions.jl HOT 3
- Implemention of Gaussian mixture model fails when sampling the posterior HOT 4
- Collision of filenames on OS X HOT 3
- Int argument for predict function HOT 2
- Follow Traditional Style Guide? (At least in public API)
- Help fitting a simple t distribution HOT 4
- For(...) do i ... broken using Soss with [email protected] or later HOT 4
- Empty model in predict HOT 6
- Modeling discrete variables
- CSV interference HOT 1
- dynamicHMC UndefVarError
- Can't use M as variable name HOT 4
- Precompilation warning HOT 2
- Example in Readme fails HOT 7
- README example fails HOT 32
- Empty transform with (new) Soss.as HOT 4
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