EU1 Model

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# Cut-and-paste code below into Window above and Run

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# EU1 SYS Model

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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)

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#Measurement Matrix  (Growth) (CO2-LU) (LU + CO2 - Q - L -N)

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#     EN.ATM.CO2E.KT EG.USE.COMM.KT.OE NY.GDP.MKTP.KD SL.TLF.TOTL.IN

#[1,]          0.316            0.4313          0.433          0.442

#[2,]          0.747            0.2760         -0.223         -0.097

#[3,]          0.352            0.0753         -0.390         -0.342

#     SP.POP.TOTL SL.UEM.TOTL.ZS

#[1,]      0.4458          0.364

#[2,]     -0.0332         -0.552

#[3,]     -0.2131          0.745

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# Fraction of Variance 

#[1] 0.828 0.972 0.996 0.999 1.000 1.000

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f <- matrix( c(  0.964467, 0.1451668,

                        0.0000000, 1.0000000

),byrow=TRUE,nrow=2,ncol=2)

h <- eye(1,2)

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

EU1 <- SS(F=f,H=h,K=k,z0=c( 0.1451668,  1.0000000),

              output.names=c("EU1"))

tfplot(simulate(EU1,sampleT=150,noise=matrix(0,150,1),start=1950))

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