Prepare Data and set parameters.

kg <- "1992-01-01::2018-03-31"
kikan <- "1992-01-01::2018-03-31"
k2k <- "2000-01-01::2018-03-31"   #GPUC model is based data only from 2000 because of cs index availability
# prepare parameters.
l <- 48  # # of months to predict
r <- 1.04 # pesumed GDP growth rate
i <- seq(2,l/3,1)  # seq of quarters to predict
d <- as.Date(as.yearqtr(seq(Sys.Date(),as.Date("2100-12-31"),by="quarters")[i])) # pick up the first day of each quarters.

getSymbols("GDP",src="FRED")
G <- GDP
m_GDP <- as.xts(as.vector(last(GDP)) * r**(i/4),d)

getSymbols("PAYEMS",src="FRED")
PA <- PAYEMS
m_PA <- (as.xts(forecast(auto.arima(PA),h=l)$mean[1:l],as.Date(as.yearmon(seq(mondate(index(last(PA)))+1,by=1,length.out=l))))[(3-month(index(last(PA))) %% 3) + seq(1,l-3,3)])[d]
PAq <- apply.quarterly(PA[k2k],mean)

getSymbols('SPCS10RSA',src='FRED')
CS <- SPCS10RSA
m_CS <-
(as.xts(forecast(auto.arima(CS),h=l)$mean[1:l],as.Date(as.yearmon(seq(mondate(index(last(CS)))+1,by=1,length.out=l))))[(3-month(index(last(CS))) %% 3) + seq(1,l-3,3)])[d]
CSq <- apply.quarterly(CS[k2k],mean)

getSymbols("UNDCONTSA",src="FRED")
# UC <- UNDCONTSA
# comment out here until UNDCONTSA update is resumed in FRED.
m_UC <- (as.xts(forecast(auto.arima(UC),h=l)$mean[1:l],as.Date(as.yearmon(seq(mondate(index(last(UC)))+1,by=1,length.out=l))))[(3-month(index(last(UC))) %% 3) + seq(1,l-3,3)])[d]
UCq <- apply.quarterly(UC[k2k],mean)