TY - CHAP A1 - Nur Iriawan A2 - Septia Devi Prihastuti Yasmirullah ED1 - Douglas McNair Y1 - 2019-11-06 PY - 2019 T1 - An Economic Growth Model Using Hierarchical Bayesian Method N2 - Bayesian networks (BN) have recently experienced increased interest and diverse applications in numerous areas, including economics, risk analysis and assets and liabilities management, AI and robotics, transportation systems planning and optimization, political science analytics, law and forensic science assessment of agency and culpability, pharmacology and pharmacogenomics, systems biology and metabolomics, psychology, and policy-making and social programs evaluation. This strong and varied response results not least from the fact that plausibilistic Bayesian models of structures and processes can be robust and stable representations of causal relationships. Additionally, BNs' amenability to incremental or longitudinal improvement through incorporating new data affords extra advantages compared to traditional frequentist statistical methods. Contributors to this volume elucidate various new developments in these aspects of BNs. BT - Bayesian Networks SP - Ch. 2 UR - https://doi.org/10.5772/intechopen.88650 DO - 10.5772/intechopen.88650 SN - 978-1-83962-323-3 PB - IntechOpen CY - Rijeka Y2 - 2021-11-30 ER -