Predictive Econometrics and Big Data

Business & Finance, Economics, Econometrics, Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Predictive Econometrics and Big Data by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319709420
Publisher: Springer International Publishing Publication: November 30, 2017
Imprint: Springer Language: English
Author:
ISBN: 9783319709420
Publisher: Springer International Publishing
Publication: November 30, 2017
Imprint: Springer
Language: English

This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems.

Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems.

Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.

More books from Springer International Publishing

Cover of the book Selected Areas in Cryptography – SAC 2017 by
Cover of the book Open Problems in Spectral Dimensionality Reduction by
Cover of the book Map Framework by
Cover of the book The British in Argentina by
Cover of the book The Front National in France by
Cover of the book Hormones in Ageing and Longevity by
Cover of the book Nietzsche and Modernism by
Cover of the book Shared Knowledge, Shared Power by
Cover of the book Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals by
Cover of the book Clinician's Manual on Migraine by
Cover of the book Smart Health by
Cover of the book The Gendered Politics of the Korean Protestant Right by
Cover of the book Search Techniques in Intelligent Classification Systems by
Cover of the book Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems by
Cover of the book Closing the Gap Between Practice and Research in Industrial Engineering by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy