TY - BOOK ID - 14734422 TI - Robustness in Econometrics AU - Kreinovich, Vladik. AU - Sriboonchitta, Songsak. AU - Huynh, Van-Nam. PY - 2017 SN - 3319507427 3319507419 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Engineering. KW - Artificial intelligence. KW - Computational intelligence. KW - Econometrics. KW - Computational Intelligence. KW - Artificial Intelligence (incl. Robotics). KW - Intelligence, Computational KW - AI (Artificial intelligence) KW - Artificial thinking KW - Electronic brains KW - Intellectronics KW - Intelligence, Artificial KW - Intelligent machines KW - Machine intelligence KW - Thinking, Artificial KW - Construction KW - Economics, Mathematical KW - Statistics KW - Artificial intelligence KW - Soft computing KW - Bionics KW - Cognitive science KW - Digital computer simulation KW - Electronic data processing KW - Logic machines KW - Machine theory KW - Self-organizing systems KW - Simulation methods KW - Fifth generation computers KW - Neural computers KW - Industrial arts KW - Technology KW - Artificial Intelligence. UR - https://www.unicat.be/uniCat?func=search&query=sysid:14734422 AB - This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations. ER -