US18 Model

# Cut-and-Paste Code Below into Window Above and Run

#

# US18 BAU Model United States

#

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  # overall-XREAL, Q-N-XREAL, Growth Cycles

#        Q      N  XREAL

#[1,] 0.585  0.527 -0.616

#[2,] 0.526 -0.825 -0.206

#[3,] 0.617  0.203  0.760

#

# Fraction of Variance 

#[1] 0.861 1.000 1.000

#

f <- matrix( c( 1.0104351906, 0.001202074, -0.001774616,  0.055307477,

                      -0.031265329, 1.018101812, -0.099887074, -0.006277844,

                    -0.0000170407, 0.005885763,  0.971462997, -0.001750443,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

),byrow=TRUE,nrow=4,ncol=4)

#

# To Stabilize, Uncomment next line

# f[1,1] <- f[2,2] <- 0.90

#

h <- eye(3,4)

k <- (f[,1:3,drop=FALSE])

US18 <- SS(F=f,H=h,K=k,z0=c(0.055307477, -0.006277844, -0.001750443,  1.0000000000),

              output.names=c("US1","US2","US3"))

print(US18)

is.SS(US18)

stability(m <- SS(F=f[1:3,1:3,drop=FALSE],Q=eye(3),R=eye(3),H=eye(3)))

# tfplot(simulate(US18,sampleT=100))

US18.data <- simulate(US18,sampleT=100,noise=matrix(0,100,3),start=1700)

US18.f <- forecast(l(US18,US18.data),horizon=150)

tfplot(US18.f)

AIC(l(US18,US18.data))

shockDecomposition(m)