One Step Ahead Forecast Comparison between pure time series ARIMA(1,0,0), Boosting and BSTS model.
# 2003-04-01 to 2007-01-01
accuracy(onestep.for.arima[1:16], yTest[1:16])
## ME RMSE MAE MPE MAPE
## Test set -0.009375665 0.3515432 0.2719274 -46.30361 205.1996
accuracy(prdBSTS[1:16], yTest[1:16])
## ME RMSE MAE MPE MAPE
## Test set -0.04146708 0.386287 0.291285 -78.174 240.7375
accuracy(prdBoost[1:16], yTest[1:16])
## ME RMSE MAE MPE MAPE
## Test set 0.08335476 0.4418408 0.3547639 -56.91056 226.384
# 2007-04-01 to 20011-01-01
gdpPreLine(time = dat.train[,1][92:107], origin = yTest[1:16], forecast1 = prdBSTS[1:16], forecast2 =onestep.for.arima[1:16], name = "arima", title = "GDP Growth, BSTS and ARIMA Forecast, 2003-2007", ylab = "Scaled GPD growth", legend = "topright")
gdpPreLine(time = dat.train[,1][92:107], origin = yTest[1:16], forecast1 = prdBSTS[1:16], forecast2 =prdBoost[1:16], name = "boosting", title = "GDP Growth, BSTS and Boosting Forecast, 2003-2007", ylab = "Scaled GPD growth", legend = "topright")
# 2007-04-01 to 2011-01-01
accuracy(onestep.for.arima[17:32], yTest[17:32])
## ME RMSE MAE MPE MAPE
## Test set -0.1599108 0.7479298 0.5077293 -653.0563 727.0223
accuracy(prdBSTS[17:32], yTest[17:32])
## ME RMSE MAE MPE MAPE
## Test set 0.002930294 0.5137749 0.4192093 -419.3927 484.3425
accuracy(prdBoost[17:32], yTest[17:32])
## ME RMSE MAE MPE MAPE
## Test set -0.1239962 0.7364592 0.528306 -786.8023 873.5214
gdpPreLine(time = dat.train[,1][92:107], origin = yTest[17:32], forecast1 = prdBSTS[17:32], forecast2 =onestep.for.arima[17:32], name = "arima", title = "GDP Growth, BSTS and ARIMA Forecast, 2007-2011", ylab = "Scaled GPD growth", legend = "bottomright")
gdpPreLine(time = dat.train[,1][92:107], origin = yTest[17:32], forecast1 = prdBSTS[17:32], forecast2 =prdBoost[17:32], name = "boosting", title = "GDP Growth, BSTS and Boosting Forecast, 2007-2011", ylab = "Scaled GPD growth", legend = "bottomright")
# 2011-04-01 to 2015-01-01
accuracy(onestep.for.arima[33:48], yTest[33:48])
## ME RMSE MAE MPE MAPE
## Test set -0.09391774 0.5088669 0.3878857 536.8736 644.3142
accuracy(prdBSTS[33:48], yTest[33:48])
## ME RMSE MAE MPE MAPE
## Test set -0.01330991 0.3968351 0.3154426 376.1166 452.209
accuracy(prdBoost[33:48], yTest[33:48])
## ME RMSE MAE MPE MAPE
## Test set -0.001741764 0.4481698 0.3112962 324.5006 404.3699
gdpPreLine(time = dat.train[,1][124:139], origin = yTest[33:48], forecast1 = prdBSTS[33:48], forecast2 =onestep.for.arima[33:48], name = "arima", title = "GDP Growth, BSTS and ARIMA Forecast, 2011-2015", ylab = "Scaled GPD growth", legend = "topright")
gdpPreLine(time = dat.train[,1][124:139], origin = yTest[33:48], forecast1 = prdBSTS[33:48], forecast2 =prdBoost[33:48], name = "boosting", title = "GDP Growth, BSTS and Boosting Forecast, 2011-2015", ylab = "Scaled GPD growth", legend = "topright")
