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British Journal of Mathematics & Computer Science, ISSN: 2231-0851,Vol.: 18, Issue.: 2

Short Communication

Scalable Functions Used for Empirical Forecasting

 

Peter Stallinga1*

1Faculty of Science and Technology, Center for Electronics Optoelectronics and Telecommunications, University of the Algarve, Portugal.

Article Information
Editor(s):
(1) Junjie Chen, Department of Electrical Engineering, University of Texas at Arlington, USA.
Reviewers:
(1) Radosaw Jedynak, Kazimierz Pulaski University of Technology and Humanities, Radom, Poland.
(2) Sanjib Kumar Datta, University of Kalyani, West Bengal, India.
(3) Anonymous, University of Delaware, USA.
Complete Peer review History: http://www.sciencedomain.org/review-history/15724

Abstracts

Empirical forecasting is the science of using past data to predict the future, without physical modeling. For these, probability functions are used, normally bell-shaped Gaussian or Gaussian- like. Taleb in his book the Black Swan introduces for this purpose the concept of scalable functions. Here it is shown that the only scalable functions are power-law functions and they can be treated as one and the same. Moreover, the analytical problems of these functions are discussed. Scalable functions are inadequate for empirical forecasting.

Keywords :

Empirical forecasting functions; extreme events; outliers; scalability.

Full Article - PDF    Page 1-6

DOI : 10.9734/BJMCS/2016/28107

Review History    Comments

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