prior.mixturescale {BayesFluxR} | R Documentation |
Scale Mixture of Gaussian Prior
Description
Uses a scale mixture of Gaussian for each network parameter. That is, the prior is given by
\pi_1 Normal(0, sigma1) + (1-\pi_1) Normal(0, sigma2)
Usage
prior.mixturescale(chain, sigma1, sigma2, pi1)
Arguments
chain |
Chain obtained using |
sigma1 |
Standard deviation of first Gaussian |
sigma2 |
Standard deviation of second Gaussian |
pi1 |
Weight of first Gaussian |
Value
a list containing the following
'juliavar' the julia variable used to store the prior
'juliacode' the julia code
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, Gamma(2.0, 0.5))
prior <- prior.mixturescale(net, 10, 0.1, 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)
sampler <- sampler.SGLD()
ch <- mcmc(bnn, 10, 1000, sampler)
## End(Not run)
[Package BayesFluxR version 0.1.3 Index]