Normal: Create a Normal Prior

In enweg/BFluxR: Implementation of Bayesian Neural Networks

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)

enweg/BFluxR documentation built on Jan. 27, 2024, 6:43 p.m.