FR1 Model

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

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# FR1 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 + EF - KOF) (LU - L - N)

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

#[1,]       0.004201            0.3740         0.3762          0.369

#[2,]       0.781330            0.0959        -0.0379         -0.059

#[3,]       0.000453            0.0585        -0.1871         -0.355

#     SP.POP.TOTL SL.UEM.TOTL.ZS     KOF     EF     HDI

#[1,]      0.3742         0.3299  0.3643 0.2460  0.3748

#[2,]     -0.0241        -0.0912 -0.1994 0.5658 -0.0815

#[3,]     -0.2225         0.8719  0.0366 0.0632 -0.1437

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# Fraction of Variance 

#[1] 0.774 0.947 0.980 0.995 0.998 0.999 1.000 1.000 1.000

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f <- matrix( c(  0.9784283, 0.1593365,

                        0.0000000, 1.0000000

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

h <- eye(1,2)

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

FR1 <- SS(F=f,H=h,K=k,z0=c( 0.1593365,  1.0000000),

              output.names=c("FR1"))

tfplot(simulate(FR1,sampleT=150,noise=matrix(0,150,1),start=1950))

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