Normal {BayesFluxR} | R Documentation |
Create a Normal Prior
Description
Creates a Normal prior in Julia using Distributions.jl. This can
then be truncated using Truncated
to obtain a prior
that could then be used as a variance prior.
Usage
Normal(mu = 0, sigma = 1)
Arguments
mu |
Mean |
sigma |
Standard Deviation |
Value
see Gamma
Examples
## Not run:
## Needs previous call to `BayesFluxR_setup` which is time
## consuming and requires Julia and BayesFlux.jl
BayesFluxR_setup(installJulia=TRUE, seed=123)
net <- Chain(Dense(5, 1))
like <- likelihood.feedforward_normal(net, Truncated(Normal(0, 0.5), 0, Inf))
## End(Not run)
[Package BayesFluxR version 0.1.3 Index]