EE_RE (0-500) Eastern Europe

# Cut-and-paste code below into the window above and Run

#

# EE_RE Eastern Europe Model Roman Empire  (RE 0-500)

#

# Measurement Matrix 

#         Q      N

#[1,] 0.707  0.707

#[2,] 0.707 -0.707

#

# Fraction of Variance 

#[1] 0.999 1.000

#

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)

f <- matrix( c( 0.9990356120, 0.008790961,  0.0095770669,

                      -0.0005332231, 1.004860640, -0.0001137029,

                        0.000000000,  0.00000000, 1.0000000000)

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

h <- eye(2,3)

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

EE_RE <- SS(F=f,H=h,K=k,z0=c(0.0095770669, -0.0001137029,  1.0000000000),

              output.names=c("EE1","EE2"))

print(EE_RE)

is.SS(EE_RE)

stability(EE_RE)

tfplot(EE_RE.data <- simulate(EE_RE,sampleT=150,start=0))

#EE_RE.data <- simulate(EE_RE,sampleT=20,noise=matrix(0,20,2))

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

tfplot(EE_RE.f)

AIC(m)

shockDecomposition(toSSChol(m))