LA_E20 Model

# Cut-and-Paste Code Below into Window Above an Run

#

# LA_E20 Model

#

# Measurement Matrix  (Growth), (Q-XREAL-X), (N-XREAL-Q)

# 

#         Q       N  XREAL        X

#[1,]  0.486  0.5062  0.501  0.50591

#[2,]  0.839 -0.0625 -0.453 -0.29580

#[3,] -0.244  0.7872 -0.566  0.00801

#

# Fraction of Variance 

#[1] 0.966 0.996 1.000 1.000

#

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

require(dse)

require(matlab)

f <- matrix( c( 1.06209533,  0.13640308, -0.1213930,  0.161979861,

                       0.01504293,  0.98769266,  0.2341202, -0.001127714,

                      -0.01330313, -0.07278229,  1.1405996, -0.011660469,

0.00000000,  0.0000000,  0.0000000,  1.0000000000

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

#

# To create a Stable model, uncomment following line

# f[1,1] <- f[2,2] <- f[3,3] <- 0.9

#

# To create a RWf model, uncomment following line

# f[1,1] <- f[2,2] <- f[3,3] <- 1

#

h <- eye(3,4)

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

LA_E20 <- SS(F=f,H=h,K=k,z0=c( 0.161979861, -0.001127714, -0.011660469,  1.0000000000),

              output.names=c("LA1","LA2","LA3"))

print(LA_E20)

is.SS(LA_E20)

stability(m0 <- SS(F=f[1:3,1:3,drop=FALSE],Q=eye(3),R=eye(3),H=eye(3)))

# LA_E20.data <- simulate(LA_E20,sampleT=50,start=1900)

 LA_E20.data <- simulate(LA_E20,sampleT=50,noise=matrix(0,50,3),start=1900)

LA_E20.f <- forecast(m <- l(LA_E20,LA_E20.data),horizon=50)

tfplot(LA_E20.f)

AIC(m)

shockDecomposition(m0,horizon=10,shock=rep(-1,10))