Diffusion-class: S4 class of model informations for diffusion process

In BaPreStoPro: Bayesian Prediction of Stochastic Processes

Description

Informations of model dY_t = b(φ,t,Y_t)dt + γ \widetilde{s}(t,Y_t)dW_t.

Slots

phi

parameter φ

gamma2

parameter γ^2

b.fun

function b(φ,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

parameter <- list(phi = 0.1, gamma2 = 0.01)
b.fun <- function(phi, t, y) phi * y
sT.fun <- function(t, y) y
start <- parameter
prior <- list(m.phi = parameter$phi, v.phi = parameter$phi^2,
   alpha.gamma = 3, beta.gamma = 2*parameter$gamma2)
model <- set.to.class("Diffusion", parameter, prior, start,
  b.fun = b.fun, sT.fun = sT.fun)

BaPreStoPro documentation built on May 2, 2019, 3:34 p.m.