OA_RE

#

# OA_RE Other Asia Model Roman Empire  (RE)

#

#Measurement Matrix 

#         Q      N

#[1,] 0.707  0.707

#[2,] 0.707 -0.707

#

# Fraction of Variance 

#[1] 0.96 1.00

#

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( 1.002523525, -0.00505709, 0.001026830,

                       0.003494434,  0.99431572, 0.001316391,

                        0.000000000,  0.00000000, 1.0000000000)

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

h <- eye(2,3)

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

OA_RE <- SS(F=f,H=h,K=k,z0=c(0.001026830, 0.001316391,  1.0000000000),

              output.names=c("OA1","OA2"))

print(OA_RE)

is.SS(OA_RE)

stability(OA_RE)

#tfplot(OA_RE.data <- simulate(OA_RE,sampleT=500,start=0))

tfplot(OA_RE.data <- simulate(OA_RE,sampleT=500,noise=matrix(0,500,2),start=0))

OA_RE.f <- forecast(m <- l(OA_RE,OA_RE.data),horizon=500)

tfplot(OA_RE.f)

AIC(m)

shockDecomposition((m))