Ricardo Cyclical

#

# Ricardo Growth and Collapse (Cut and paste code into window above and Run (Cmd-Enter)

#

merge.forecast <- function (fx,n=1) {

x <- splice(fx$pred,fx$forecast[[n]])

colnames(x) <- seriesNames(fx$data$output)

return(x)

}

AIC <- function(model) {informationTestsCalculations(model)[3]}

require(dse)

require(matlab)

#

# Measurement Matrix (Growth) (Q-K-L) (Growth)

#          K      L     Q

#[1,]  0.579  0.579 0.573

#[2,] -0.405 -0.405 0.819

#

# Fraction of Variance 

#[1] 0.986 1.000 1.000

#

f <- matrix( c(0.98473990, 1.2485612, 0.002954592,

                    -0.01800149, 0.9864476, 0.001209771,

0.00000000,  0.0000000, 1.0000000000

),byrow=TRUE,nrow=3,ncol=3)

h <- eye(2,3)

k <- (f[,1:2,drop=FALSE])

Ricardo <- SS(F=f,H=h,K=k,z0=c(0.002954592, 0.001209771,  1.0000000000),

              output.names=c("Ricardo1","Ricardo2"))

print(Ricardo)

is.SS(Ricardo)

stability(SS(F=f[1:2,1:2,drop=FALSE],H=eye(2),Q=eye(2),R=eye(2)))

# tfplot(simulate(Ricardo,sampleT=100))

Ricardo.data <- simulate(Ricardo,sampleT=100,noise=matrix(0,100,2))

Ricardo.f <- forecast(l(Ricardo,Ricardo.data),horizon=150)

tfplot(Ricardo.f)

AIC(l(Ricardo,Ricardo.data))