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Approximate Method of Estimation of Exponential Trend Parameters for Forecasting Process Purposes Cover

Approximate Method of Estimation of Exponential Trend Parameters for Forecasting Process Purposes

Open Access
|Jul 2018

Abstract

The paper discusses the issue of estimation of exponential trend parameters in terms of its application in the forecast process. Due to the character of a random element, three models were considered: additive, multiplicative, and mixed. For estimating trend parameters, a log transformation method, least squares method, and approximate methods were applied. As a result of computer simulations, high sensitivity of the log transformation method with regard to the assumed random element model was noticed. This method yields the smallest value of ex post error for the multiplicative model but is burdened with a large error for the additive model, where the estimated parameter B takes large values (B > 0.24). In the paper, a new approximate method of estimation of exponential trend parameters is proposed. The method is compared with approximate formulas presented in the paper by Purczyński (2008).

DOI: https://doi.org/10.2478/foli-2018-0013 | Journal eISSN: 1898-0198 | Journal ISSN: 1730-4237
Language: English
Page range: 169 - 181
Submitted on: Oct 30, 2017
Accepted on: Mar 27, 2018
Published on: Jul 4, 2018
Published by: University of Szczecin
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2018 Kamila Bednarz-Okrzyńska, published by University of Szczecin
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.