BayesFluxR (version 0.1.3)

initialise.allsame: Initialises all parameters of the network, all hyper parameters of the prior and all additional parameters of the likelihood by drawing random values from `dist`.

Description

Initialises all parameters of the network, all hyper parameters of the prior and all additional parameters of the likelihood by drawing random values from `dist`.

Usage

initialise.allsame(dist, like, prior)

Value

A list containing the following

• `juliavar` - julia variable storing the initialiser

• `juliacode` - julia code used to create the initialiser

Arguments

dist

A distribution; See for example Normal

like

A likelihood; See for example likelihood.feedforward_normal

prior

A prior; See for example prior.gaussian

Examples

if (FALSE) {
  ## 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, Gamma(2.0, 0.5))
  prior <- prior.gaussian(net, 0.5)
  init <- initialise.allsame(Normal(0, 0.5), like, prior)
  x <- matrix(rnorm(5*100), nrow = 5)
  y <- rnorm(100)
  bnn <- BNN(x, y, like, prior, init)
  BNN.totparams(bnn)
}