利用虚拟变量评估沙特阿拉伯1979-2011年降水回归模型

Q4 Social Sciences
Manahil Eltayeb, Sulafa Hag-elsafi
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引用次数: 0

摘要

目的:本研究旨在通过设计基于王国20个站点1979年至2011年数据的模型来分析沙特阿拉伯的降雨量。方法:采用以降雨量为因变量,以季度为自变量的多元线性回归模型进行分析。在分析中使用了虚拟变量。回归模型对沙特阿拉伯不同地区降雨率的影响提供了有价值的见解。在研究期间,从王国的每个地区收集每月数据,并根据平均降雨量分为五组:第1组(5-15毫米),第2组(15-25毫米),第3组(25-35毫米),第4组(35-45毫米)和第5组(45-70毫米)。每组用一个单独的回归模型表示。为了减少模型中虚拟变量的数量,将月度数据转换为季度数据。结果:本研究的一个重要发现是,所有模型都具有统计显著性,表明降雨量分布受年度季度的影响。此外,我们观察到,除了第5组的第4季度和第1、2、4组的第3季度,不同地区的大多数季度的平均降雨量在统计上都是显著的。结论:将虚拟变量作为自变量纳入多元线性回归模型是分析降雨时间序列的一种新颖有效的方法。这些结果可以作为未来研究的基础,使人们能够根据研究结果进行预测和明智的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of Regression Model for Rainfall in Saudi Arabia (1979-2011) Using Dummy Variables
Objectives: This study aims to analyze rainfall in Saudi Arabia by designing models based on data from 20 stations across the Kingdom from 1979 to 2011. Methods: The analysis employed a multiple linear regression model with rainfall as the dependent variable and annual quarters as the independent variables. Dummy variables were utilized in the analysis. The regression model provided valuable insights into the impact of rainfall rates in different quarters across Saudi Arabia. Monthly data was collected from each region of the Kingdom during the study period and categorized into five groups based on average rainfall: Group 1 (5-15 mm), Group 2 (15-25 mm), Group 3 (25-35 mm), Group 4 (35-45 mm), and Group 5 (45-70 mm). Each group was represented by a separate regression model. To reduce the number of dummy variables in the model, the monthly data was converted to quarterly data. Results: A significant finding of this study is that all models were statistically significant, indicating that rainfall distribution is influenced by the annual quarters. Furthermore, it was observed that the average rainfall in most quarters across different regions was statistically significant, except for the fourth quarter in Group 5 and the third quarter in Groups 1, 2, and 4. Conclusions: The inclusion of dummy variables as independent variables in the multiple linear regression model proved to be a novel and effective approach for analyzing rainfall time series. The results can serve as a foundation for future studies, enabling prediction and informed decision-making based on the findings.
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来源期刊
Dirasat: Human and Social Sciences
Dirasat: Human and Social Sciences Arts and Humanities-Arts and Humanities (miscellaneous)
CiteScore
0.10
自引率
0.00%
发文量
207
期刊介绍: Dirasat is an international peer-refereed research journal published in seven specialized series by the Deanship of Academic Research, University of Jordan. Issues of Dirasat: Human and Social Sciences are published tri-annually. Articles submitted are reviewed according to the highest standards by scientists specialized in their fields. The articles are written in Arabic or English.
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