New method of randomized forecasting using entropy-robust estimation: application to the world population prediction
type: Item
instance of: scholarly article
title: New method of randomized forecasting using entropy-robust estimation: application to the world population prediction
zbMATH Open document ID: 1419.62263
author: Yuri S. Popkov
author: Yuri A. Dubnov
author: Alexey Yu. Popkov
published in: Mathematics
publication date: 2016-04-20T00:00:00Z
review text: Summary: 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.
Mathematics Subject Classification ID: 62M20
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 91B84
Mathematics Subject Classification ID: 62P25
Mathematics Subject Classification ID: 91D20
zbMATH DE Number: 6571027
zbMATH Keywords: entropy
zbMATH Keywords: randomized model
zbMATH Keywords: randomized forecasting
zbMATH Keywords: exponential world population model
MaRDI profile type: Publication
full work available at URL: math4010016
OpenAlex ID: W2294738752
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DOI: 10.3390/MATH4010016
description: scientific article; zbMATH DE number 6571027