#
# Cut-and-Paste Code below into Window Above and Run
#
# WMA (Middle Ages) Model -> W_MA_CHACO Chaco Canyon Model
#
merge.forecast <- function (fx,n=1) {
x <- splice(fx$pred,fx$forecast[[n]])
colnames(x) <- seriesNames(fx$data$output)
return(x)
}
#
# Measurement Matrix (Growth-T), (Growth), (Q-N)
# Q N T
#[1,] 0.666 0.689 -0.286
#[2,] 0.290 0.115 0.950
#[3,] 0.688 -0.716 -0.123
#
# Fraction of Variance
#
AIC <- function(model) {informationTestsCalculations(model)[3]}
require(dse)
require(matlab)
f <- matrix( c(1.009209e+00, -5.212984e-03, -2.7763749, 6.644212e-03,
2.775262e-03, 9.984308e-01, -0.8367732, -1.637815e-03,
6.840086e-06, 9.757525e-06, 0.9970411, 5.546619e-06,
0.00000000, 0.0000000, 0.0000000, 1.0000000000
),byrow=TRUE,nrow=4,ncol=4)
#
# To stabilize, Uncomment next line
# f[1,1] <- f[2,2] <- f[3,3] <- .9
#
h <- eye(3,4)
k <- (f[,1:3,drop=FALSE])
WMA <- SS(F=f,H=h,K=k,z0=c( 6.644212e-03, -1.637815e-03, 5.546619e-06, 1.0000000000),output.names=c("W1","W2","W3"))
m <- SS(F=f[1:3,1:3,drop=FALSE],Q=eye(3),R=eye(3),H=eye(3))
stability(m)
WMA.data <- simulate(WMA,sampleT=100,start=500)
# WMA.data <- simulate(WMA,sampleT=20,noise=matrix(0,20,3)
WMA.f <- forecast(m <- l(WMA,WMA.data),horizon=50)
WMA.fx <- merge.forecast(WMA.f)
#tfplot(WMA.f)
#
#
# W_MA_CHACO Chaco Canyon Model
#
#
#
#Measurement Matrix
#
# (Growth) (T-GROWTH) (Q-N-T)
# N Q T
#[1,] 0.580 0.630 0.517
#[2,] -0.564 -0.148 0.813
#[3,] -0.588 0.763 -0.269
#
# Fraction of Variance
#[1] 0.772 0.960 1.000
#
f <- matrix( c(0.997159105, 0.01780180, 0.1557398, -1.9230687,
0.007181947, 1.02963680, 0.1772908, -0.8128624,
0.001295940, -0.02003162, 0.9328308, 0.5772216,
0.000000000, 0.00000000, 0.0000000, 1.0000000
),byrow=TRUE,nrow=4,ncol=4)
h <- eye(3,4)
k <- (f[,1:3,drop=FALSE])
g <- matrix( c(
3.1646991, 2.3178546, 144.29550,
1.5717685, 1.1760817, 3.61204,
-0.9785195, -0.7014869, -40.38529,
0.0000000, 0.0000000, 0.00000
),byrow=TRUE,nrow=4,ncol=3)
#
WMAC <- SS(F=f,H=h,K=k,z0=c( -0.033015420, -0.012519378, 0.006011046, 1),output.names=c("CHACO1","CHACO2","CHACO3"))
m <- SS(F=f[1:3,1:3,drop=FALSE],Q=eye(3),R=eye(3),H=eye(3))
stability(m)
WMAC.data <- simulate(WMAC,sampleT=100,start=500,input=WMA.fx)
#WMAC.data <- simulate(WMAC,sampleT=20,noise=matrix(0,20,3),start=500,inputs=WMA.fx)
tfplot(WMAC.data)