Boundary for Turing parameters

General Usage
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4

I think you can use the truncated function (defined in Distributions.jl) on the distribution and the keyword arguments lowerand upper like this

    b ~ truncated(Normal(1.5, 1.0); lower = -10, upper = 10)
    s  ~ truncated(Normal(0.1, 1.0); lower = -1, upper = 1)
    q  ~ truncated(Normal(0.7, 1.0); lower = -1, upper = 1)

This means it’s physically/mathematically impossible for the parameters to be outside the intervals (prior assumption/knowledge).