USL20 Egg Prices

#

# USL20 TECH

#

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)

f <- matrix( c(1.011058, 0.1774866,

                      0.000000, 1.0000000

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

h <- eye(1,2)

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

TECH <- SS(F=f,H=h,K=k,z0=c( 0.1774866, 1.0000000),

     output.names=c("TECH"))

print(TECH)

is.SS(TECH)

stability(TECH)

# help(simulate)

TECH.data <- simulate(TECH,sampleT=100,

                       start=1950)

seriesNames(outputData(TECH.data)) <- c("TECH")

AIC(TECH.model <- l(TECH,TECH.data))

shockDecomposition(toSSChol(TECH.model))

tfplot(TECH.f <- forecast(TECH.model,horizon=50))

TECH.fx <- merge.forecast(TECH.f )

#

# Price of Eggs

#

f <- matrix( c(0.184328, -0.7947243,

                      0.000000, 1.0000000

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

g <- matrix(c(0.06589205,

                     0.0000000

),nrow=2,ncol=1, byrow=TRUE)

h <- eye(1,2)

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

P_EGGS <- SS(F=f,H=h,K=k,z0=c( 0.4934786, 1.0000000),

     output.names=c("P(EGGS)"))

print(P_EGGS)

is.SS(P_EGGS)

stability(P_EGGS)

# help(simulate)

P_EGGS.data <- simulate(P_EGGS,sampleT=150,input=TECH.fx,

                       start=1950)

seriesNames(outputData(P_EGGS.data)) <- c("P(EGGS)")

tfplot(P_EGGS.data)

AIC(P_EGGS.model <- l(P_EGGS,P_EGGS.data))

shockDecomposition(toSSChol(P_EGGS.model))