initialise.allsame {BayesFluxR} | R Documentation |
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'.
initialise.allsame(dist, like, prior)
dist |
A distribution; See for example |
like |
A likelihood; See for example |
prior |
A prior; See for example |
A list containing the following
'juliavar' - julia variable storing the initialiser
'juliacode' - julia code used to create the initialiser
## 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, 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)
## End(Not run)