WE_RE Model (0-500) Western Europe

# Cut-and-Paste code below into window above and Run

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# WE_RE Western Europe Model Roman Empire  (RE 0-500)

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#Measurement Matrix 

#         Q      N

#[1,] 0.707 -0.707

#[2,] 0.707  0.707

#

# Fraction of Variance 

#[1] 0.989 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( 0.996631447, -0.01749514, 0.0088050680,

                       0.001398781,  1.00726480, 0.0005028044,

                        0.000000000,  0.00000000, 1.0000000000)

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

h <- eye(2,3)

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

WERE <- SS(F=f,H=h,K=k,z0=c(0.0088050680, 0.0005028044,  1.0000000000),

              output.names=c("WE1","WE2"))

print(WERE)

is.SS(WERE)

stability(WERE)

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

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

WERE.f <- forecast(m <- l(WERE,WERE.data),horizon=50)

tfplot(WERE.f)

AIC(m)

shockDecomposition(toSSChol(m))