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library(Sim.DiffProc)
## Application to real data
## CKLS modele vs CIR modele
## CKLS (mod1): dX(t) = (theta1+theta2* X(t))* dt + theta3 * X(t)^theta4 * dW(t)
## CIR (mod2): dX(t) = (theta1+theta2* X(t))* dt + theta3 * sqrt(X(t)) * dW(t)
set.seed(1234)
data(Irates)
rates <- Irates[,"r1"]
rates <- window(rates, start=1964.471, end=1989.333)
fx1 <- expression(theta[1]+theta[2]*x)
gx1 <- expression(theta[3]*x^theta[4])
gx2 <- expression(theta[3]*sqrt(x))
fitmod1 <- fitsde(rates,drift=fx1,diffusion=gx1,pmle="euler",start = list(theta1=1,theta2=1,
theta3=1,theta4=1),optim.method = "L-BFGS-B")
fitmod2 <- fitsde(rates,drift=fx1,diffusion=gx2,pmle="euler",start = list(theta1=1,theta2=1,
theta3=1),optim.method = "L-BFGS-B")
summary(fitmod1)
summary(fitmod2)
coef(fitmod1)
coef(fitmod2)
confint(fitmod1,parm=c('theta2','theta3'))
confint(fitmod2,parm=c('theta2','theta3'))
AIC(fitmod1)
AIC(fitmod2)
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