Forecast combination based reconciliation of the monthly Australian Tourism Demand series disaggregated by geographic divisions and purpose of travel (Di Fonzo and Girolimetto, 2024)
The forecast reconciliation is performed using FoReco 0.2.2.
VN525.RData
: Australian Tourism Flows dataset (Visitor Nights)Ctools555.RData
: tools to balance the C matrix (VN525 -> VN555)- BaseForecasts:
ETSlev/VN525_base_ets_lev.R
: ETS base forecastsETSlev/VN555/VN555_base.R
: VN555 ETS levels and SA base forecastsVN525_features_residuals.R
: Seasonal Average residualsVN525_features.R
: Seasonal Average forecasts
- Reconciliation:
ETSlev
:VN555_cslccd_bCCCred.R
: LCC with ETS bts (exogenous)VN555_cslccd_bLCC.R
: LxCC with ETS bts (x = level number, exogenous)VN555_cslccd_bLCCendo.R
: LxCC with ETS bts (x = level number, endogenous)VN555_cslccd_bCCCred_endo.R
: LCC with ETS bts (endogenous)VN555_cslccd_mean_red.R
: LCC with SA bts (exogenous)VN555_cslccd_mean_red_endo.R
: LCC with SA bts (endogenous)VN555_cslccd_mean.R
: CCC with SA bts (exogenous and endogenous)VN555_cslccd_mLCC.R
: LxCC with SA bts (x = level number, exogenous)VN555_cslccd_mLCCendo.R
: LxCC with SA bts (x = level number, endogenous)VN555_cslccd.R
: CCC with ETS bts and CCCH (exogenous and endogenous)VN525_htsrec_mean.R
: cross-sectional reconciliation with SA btsVN525_htsrec.R
: cross-sectional reconciliation with ETS btsVN555_CCCmix_red.R
: sample average of LCC (SA + ETS bts, exogenous)VN555_CCCmix_red_endo.R
: sample average of LCC (SA + ETS bts, endogenous)VN555_CCCmix.R
: sample average of CCC (SA + ETS bts, exogenous)VN555_CCCmix_endo.R
: sample average of CCC (SA + ETS bts, endogenous)VN525_csmix.R
: sample average of the cross-sectional reconciliation (SA + ETS bts)
function
: functions forscore/VN525_scores_ETSlev.R
score/VN525_scores_ETSlev.R
: returns the scores’ dataset
Di Fonzo, T. and Girolimetto D. (2024). Forecast combination based forecast reconciliation: insights and extensions, International Journal of Forecasting, 40(2), pp. 490-514. doi:10.1016/j.ijforecast.2022.07.00