DEL20 Model

#

# DEL20 BAU Model

# Cut-and-paste the following code into the window above and Run (Cmd-Enter)

#

#Measurement Matrix 

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

#[1,]          0.333            0.3207         0.3460          0.360

#[2,]          0.286            0.4125        -0.2792         -0.119

#[3,]         -0.603            0.0753        -0.0969         -0.198

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

#[1,]       0.344          0.348  0.361 0.206  0.353

#[2,]      -0.192         -0.226 -0.048 0.722 -0.213

#[3,]       0.620         -0.105  0.324 0.230 -0.168

# Fraction of Variance 

#[1] 0.827 0.968 0.987 0.994 0.997 0.999 1.000 1.000 1.000

#

AIC <- function(model) {informationTestsCalculations(model)[3]}

require(dse)

require(matlab)

f <- matrix( c(0.95349473,  0.01511665, 0.09597823, 0.165278528,

                     -0.03688928,  0.94701798, 0.14835340, 0.006940459,

                      -0.01833974, -0.06112404, 0.89684472, 0.020441322,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

),byrow=TRUE,nrow=4,ncol=4)

h <- eye(3,4)

k <- (f[,1:3,drop=FALSE])

DEL20 <- SS(F=f,H=h,K=k,z0=c(0.165278528, 0.006940459, 0.020441322,  1.0000000000),

              output.names=c("DE1","DE2","DE3"))

print(DEL20)

is.SS(DEL20)

stability(DEL20)

# tfplot(simulate(DEL20,sampleT=100))

DEL20.data <- simulate(DEL20,sampleT=50,noise=matrix(0,20,3))

DEL20.f <- forecast(m <- l(DEL20,DEL20.data),horizon=50)

tfplot(DEL20.f)

AIC(m)