Merton-class {BaPreStoPro} | R Documentation |
Informations of model dY_t = φ Y_t dt + γ^2 Y_t dW_t + θ Y_tdN_t with N_t\sim Pois(Λ(t, ξ)). The explicit solution of the SDE is given by Y_t = y_0 \exp( φ t - γ^2/2 t+γ W_t + \log(1+θ) N_t).
thetaT
parameter \widetilde{θ}=\log(1+θ)
phi
parameter φ
gamma2
parameter γ^2
xi
parameter ξ
Lambda
function Λ(t,ξ)
prior
list of prior parameters for φ, \widetilde{θ}, γ^2
priorDensity
list of prior density function for ξ
start
list of starting values for the Metropolis within Gibbs sampler
parameter <- list(phi = 0.01, thetaT = 0.1, gamma2 = 0.01, xi = c(2, 0.2)) Lambda <- function(t, xi) (t / xi[2])^xi[1] # prior density for xi: priorDensity <- function(xi) dgamma(xi, c(2, 0.2), 1) # prior parameter for phi (normal), thetaT (normal) and gamma2 (inverse gamma): prior <- list(m.phi = parameter$phi, v.phi = parameter$phi, m.thetaT = parameter$thetaT, v.thetaT = parameter$thetaT, alpha.gamma = 3, beta.gamma = parameter$gamma2*2) start <- parameter model <- set.to.class("Merton", parameter, prior, start, Lambda = Lambda, priorDensity = priorDensity) summary(class.to.list(model)) # default: model <- set.to.class("Merton", parameter, Lambda = Lambda)