BaPreStoPro (version 0.1)

mixedDiffusion-class: S4 class of model informations for hierarchical (mixed) diffusion process model

Description

Informations of model $dY_t = b(\phi_j,t,Y_t)dt + \gamma \widetilde{s}(t,Y_t)dW_t, \phi_j\sim N(\mu, \Omega), Y_{t_0}=y_0(\phi, t_0)$.

Slots

phi

parameter $\phi$

mu

parameter $\mu$

Omega

parameter $\Omega$

gamma2

parameter $\gamma^2$

y0.fun

function $y_0(\phi, t)$

b.fun

function $b(\phi,t,y)$

sT.fun

function $\widetilde{s}(t,y)$

prior

list of prior parameters

start

list of starting values for the Metropolis within Gibbs sampler

Examples

mu <- c(2, 1); Omega <- c(1, 0.04)
phi <- sapply(1:2, function(i) rnorm(21, mu[i], sqrt(Omega[i])))
parameter <- list(phi = phi, mu = mu, Omega = Omega, gamma2 = 0.01)
b.fun <- function(phi, t, y) phi[1] * y
sT.fun <- function(t, y) y
y0.fun <- function(phi, t) phi[2]
start <- parameter
prior <- list(m.mu = parameter$mu, v.mu = parameter$mu^2,
   alpha.omega = rep(3, length(parameter$mu)), beta.omega = parameter$Omega*2,
   alpha.gamma = 3, beta.gamma = parameter$gamma2*2)
model <- set.to.class("mixedDiffusion", parameter, prior, start,
  b.fun = b.fun, sT.fun = sT.fun, y0.fun = y0.fun)