ANALYSIS OF TIME SERIES USING COMPLEX ECONOMIC-MATHEMATICAL METHODS
Article Sidebar
Main Article Content
Abstract
This article covers the stages of determining nonlinear trends in time series, mathematical modeling, finding trend equations using regression methods, and forecasting. In particular, taking into account the complex dynamics of economic processes, the advantages of exponential, logarithmic, and polynomial models are analyzed. The accuracy and error criteria of forecast results are considered through practical examples.
Downloads
Article Details
Section
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.
How to Cite
References
1.Tursunov BX Modeling of economic processes. – Tashkent: Economics, 2017. – 280 p.
2.Tokhtasinov Sh.T. Statistics and economic analysis. – Tashkent: Fan, 2020. – 320 p.
3.Gujarati, DN Basic Econometrics . – 5th Edition. - McGraw-Hill, 2009. - 924 p.
4.Box, GEP, Jenkins, GM, & Reinsel, GC Time Series Analysis: Forecasting and Control . – 5th Edition. – Wiley, 2015. – 712 p.