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Mathematics 2016, 4(1), 16; doi:10.3390/math4010016

New Method of Randomized Forecasting Using Entropy-Robust Estimation: Application to the World Population Prediction

1
Institute for Systems Analysis of Russian Academy of Sciences, Moscow 117312, Russia
2
Moscow Institute of Physics and Technology (State University), Moscow 141700, Russia
3
National Research University Higher School of Economics, Moscow 101000, Russia
*
Author to whom correspondence should be addressed.
Academic Editor: Hari M. Srivastava
Received: 13 October 2015 / Revised: 25 January 2016 / Accepted: 4 March 2016 / Published: 11 March 2016
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Abstract

We propose a new method of randomized forecasting (RF-method), which operates with models described by systems of linear ordinary differential equations with random parameters. The RF-method is based on entropy-robust estimation of the probability density functions (PDFs) of model parameters and measurement noises. The entropy-optimal estimator uses a limited amount of data. The method of randomized forecasting is applied to World population prediction. Ensembles of entropy-optimal prognostic trajectories of World population and their probability characteristics are generated. We show potential preferences of the proposed method in comparison with existing methods. View Full-Text
Keywords: entropy; randomized model; randomized forecasting; the exponential World population model entropy; randomized model; randomized forecasting; the exponential World population model
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Popkov, Y.S.; Dubnov, Y.A.; Popkov, A.Y. New Method of Randomized Forecasting Using Entropy-Robust Estimation: Application to the World Population Prediction. Mathematics 2016, 4, 16.

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