WL20_AXIS

#

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

#

# help(dse)

# help(SS)

#

# AXIS BAU Growth

#

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

require(dse)

require(matlab)

#

# Measurement Matrix 

#       RU1    IN1    CN1

#[1,] 0.514  0.601  0.612

#[2,] 0.855 -0.414 -0.311

#

# Fraction of Variance 

#[1] 0.843 0.994 1.000

#

f <- matrix( c(   1.01460086, -0.03779872, 0.115936692,

                       -0.01948855,  0.96412537, 0.009885037,

                         0.00000000,  0.00000000, 1.000000000

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

#

# To stabilize, uncomment the next line

# f[1,1] <- 0.98; f[2,2] <- 0.94

#

h <- eye(2,3)

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

AXIS <- SS(F=f,H=h,K=k,z0=c(  0.115936692, 0.009885037, 1.000000000),

output.names=c("AXIS1", "AXIS2"))

print(AXIS)

is.SS(AXIS)

stability(AXIS)

AXIS.data <- simulate(AXIS,sampleT=150,noise=matrix(0,150,2),start=1960)

tfplot(AXIS.data)

AXIS.f <- forecast(l(AXIS,AXIS.data),horizon=150,start=1960)

tfplot(AXIS.f)

AIC(l(AXIS,AXIS.data))

shockDecomposition(toSSChol(AXIS))