Mathematical Modeling and Forecasting of Economic Variables Based on Linear Regression Statistics

被引：1

作者：

Huang, Jiong ^{[1
,2
]}

Aldeeb, Horiya ^{[3
]}

机构：

[1] Kunming Univ Sci & Technol, Sch Management & Econ, Kunming 650092, Yunnan, Peoples R China

[2] Yunnan Normal Univ, Sch Math, Kunming 650500, Yunnan, Peoples R China

[3] Appl Sci Univ, Coll Adm Sci, Al Ekir, Bahrain

来源：

APPLIED MATHEMATICS AND NONLINEAR SCIENCES | 2023年 / 8卷 / 01期

关键词：

Linear regression analysis; Economic variables; Gross regional product; Mathematical modeling;

D O I：

10.2478/amns.2022.2.00023

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Many economic variables are interdependent, restrictive, and influential. Finding the law of change between economic variables and influencing factors and expressing this law in mathematical expressions will bring great convenience to forecasting. A statistical analysis method that uses mathematical equations to determine the quantitative relationship between two or more variables. This is more commonly used when estimating and predicting the value of the dependent variable. The article analyzes the data on the National Bureau of Statistics website and uses the method of multiple linear regression to fit the graphs of economic indicators. Finally, the forecast data is analyzed in detail. We evaluated the modeling method of the prediction model and the credibility of the prediction data from a practical level.

引用

页码：409 / 416

页数：8

共 50 条

[1] Modeling and forecasting electricity prices based on linear regression method
Huang, Yuehua
Gao, Mei-ling
[J]. PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON MODELLING AND SIMULATION (ICMS2009), VOL 6, 2009, : 341 - 347
[2] Forecasting economic growth using financial variables - Comparison of linear regression and neural network models
Marijana, Curak
Poposki, Klime
Ivan, Curak
[J]. MICBE '09: PROCEEDINGS OF THE 10TH WSEAS INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN BUSINESS AND ECONOMICS, 2009, : 255 - +
[3] Modeling and forecasting mortality with economic, environmental and lifestyle variables
Dimai, Matteo
[J]. DECISIONS IN ECONOMICS AND FINANCE, 2024,
[4] Statistics and economic forecasting
Burns, EM
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1929, 24 (166) : 152 - 163
[5] FORECASTING ECONOMIC VARIABLES
BRODE, J
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1969, 64 (326) : 691 - &
[6] A Simple Linear Regression Approach to Modeling and Forecasting Mortality Rates
Lin, Tzuling
Tsai, Cary Chi-Liang
[J]. JOURNAL OF FORECASTING, 2015, 34 (07) : 543 - 559
[7] MATHEMATICAL MODELING OF THERMAL DESORPTION USING LINEAR REGRESSION ANALYSIS
Prodan, Calin Vasile
Micle, Valer
Rogozan, George Calin
Prodan, Maria
[J]. ENVIRONMENTAL ENGINEERING AND MANAGEMENT JOURNAL, 2013, 12 (02): : 365 - 369
[8] Wavelet Bootstrap Multiple Linear Regression Based Hybrid Modeling for Daily River Discharge Forecasting
Sehgal, Vinit
Tiwari, Mukesh K.
Chatterjee, Chandranath
[J]. WATER RESOURCES MANAGEMENT, 2014, 28 (10) : 2793 - 2811
[9] Wavelet Bootstrap Multiple Linear Regression Based Hybrid Modeling for Daily River Discharge Forecasting
Vinit Sehgal
Mukesh K. Tiwari
Chandranath Chatterjee
[J]. Water Resources Management, 2014, 28 : 2793 - 2811
[10] Historical forms of development of mathematical modeling as a system for forecasting economic activity
Olim, Astanakulov T.
Akhmed, Gachaev M.
Vladimir, Shinkaruk M.
Tatyana, Abalakina, V
[J]. VOPROSY ISTORII, 2021, 6 (02) : 87 - 94

← 1 2 3 4 5 →