Forecasting GDP in ASIAN Countries Using Relevant Vector Machines

Somsak Chanaim, Wilawan Srichaikul, Chongkolnee Rungruang, Songsak Sriboonchitta

Abstract

The relevance vector machine(RVM) is applied to predict  GDP, the highly important measurement of national economic growth, of some ASEAN countries (Malaysia, Thailand and Singapore) for comparison with the autoregressive model (AR(p)). The results show that RVM dominates the AP(p) model by measuring the error (MAE, MAPE, MSE and RMSE) from both training data and validation data.