EUL20 Model

# Cut-and-Paste Code Below into Window above and Run

#

# EUL20 Model

#

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

require(dse)

require(matlab)

#

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

#     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

#

# Fraction of Variance 

#[1] 0.828 0.972 0.996 0.999 1.000 1.000

f <- matrix( c(0.964430034, -7.321276e-05, 0.01413639,  0.1450974567,

                     -0.053232046,  9.697933e-01, 0.04289553,  0.0008440534,

                      -0.005985813, 8.425407e-04, 0.93190290, -0.0031522950,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

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

h <- eye(3,4)

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

EUL20 <- SS(F=f,H=h,K=k,z0=c(0.1450974567,  0.000844053,4 -0.0031522950,  1.0000000000),

              output.names=c("EU1","EU2","EU3"))

print(EUL20)

is.SS(EUL20)

stability(SS(F=f[1:3,1:3,drop=FALSE],R=eye(3),Q=eye(3,3),H=eye(3,3)))

# tfplot(simulate(EUL20,sampleT=100))

EUL20.data <- simulate(EUL20,sampleT=50,noise=matrix(0,50,3),start=1960)

EUL20.f <- forecast(m <- l(EUL20,EUL20.data),horizon=150)

tfplot(EUL20.f)