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

Yuri S. Popkov, Yuri A. Dubnov and Alexey Yu. Popkov
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Yuri S. Popkov: Institute for Systems Analysis of Russian Academy of Sciences, Moscow 117312, Russia
Yuri A. Dubnov: Institute for Systems Analysis of Russian Academy of Sciences, Moscow 117312, Russia
Alexey Yu. Popkov: Institute for Systems Analysis of Russian Academy of Sciences, Moscow 117312, Russia

Mathematics, 2016, vol. 4, issue 1, 1-16

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.

Keywords: entropy; randomized model; randomized forecasting; the exponential World population model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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