The current financial education framework has an increasing need to introduce tools that facilitate the application of theoretical models to real-world data and contexts.However,only a limited number of free tools are...The current financial education framework has an increasing need to introduce tools that facilitate the application of theoretical models to real-world data and contexts.However,only a limited number of free tools are available for this purpose.Given this lack of tools,the present study provides two approaches to facilitate the implementa-tion of an event study.The first approach consists of a set of MS Excel files based on the Fama–French five-factor model,which allows the application of the event study methodology in a semi-automatic manner.The second approach is an open-source R-programmed tool through which results can be obtained in the context of an event study without the need for programming knowledge.This tool widens the calculus possibilities provided by the first approach and offers the option to apply not only the Fama–French five-factor model but also other models that are common in the finan-cial literature.It is a user-friendly tool that enables reproducibility of the analysis and ensures that the calculations are free of manipulation errors.Both approaches are freely available and ready-to-use.展开更多
本文阐述了数据可视化的发展、定义以及作用等基本知识。利用R语言与BDP(Business Data Platform)商业数据平台对中国地震台网近一年3.0级以上地震进行可视化处理。首先进行数据爬取,对数据进行清洗;其次进行R语言的数据可视化;最后利用...本文阐述了数据可视化的发展、定义以及作用等基本知识。利用R语言与BDP(Business Data Platform)商业数据平台对中国地震台网近一年3.0级以上地震进行可视化处理。首先进行数据爬取,对数据进行清洗;其次进行R语言的数据可视化;最后利用BDP平台提供的地理信息系统功能,将地震数据与地理空间信息相结合,生成了地震热力图、地震点分布图等可视化效果。实验结果表明,基于R语言与BDP的地震数据可视化方法具有较好的效果和可行性。可视化分析揭示了地震活动的空间分布特征和时序变化规律,为地震预测和防灾工作提供了重要参考。展开更多
本文收集了广州地区2003年至2022年的中医药卫生技术人员和医院床位数等数据,采用R语言构建自回归整合移动平均模型(Autoregressive Integrated Moving Average Model,ARIMA)进行中医药卫生资源配置预测研究,分析了广州市中医药卫生资...本文收集了广州地区2003年至2022年的中医药卫生技术人员和医院床位数等数据,采用R语言构建自回归整合移动平均模型(Autoregressive Integrated Moving Average Model,ARIMA)进行中医药卫生资源配置预测研究,分析了广州市中医药卫生资源的情况以及发展趋势,为广州市相关中医药卫生政策制定提供参考依据。展开更多
This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and i...This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and its powerful data management and analysis tools make it suitable for handling complex data analysis tasks.It is also highly customizable,allowing users to create custom functions and packages to meet their specific needs.Additionally,R language provides high reproducibility,making it easy to replicate and verify research results,and it has excellent collaboration capabilities,enabling multiple users to work on the same project simultaneously.These advantages make R language a more suitable choice for complex data analysis tasks,particularly in scientific research and business applications.The findings of this study will help people understand that R is not just a language that can handle more data than Excel and demonstrate that r is essential to the field of data analysis.At the same time,it will also help users and organizations make informed decisions regarding their data analysis needs and software preferences.展开更多
目的:探讨基于R语言构建的自回归滑动平均模型(autoregressive integrated moving average model,ARIMA)对医用耗材消耗量的预测效果。方法:选取某类预冲式冲管注射器2018年7月至2023年6月月度消耗量数据作为样本数据,利用R语言对样本...目的:探讨基于R语言构建的自回归滑动平均模型(autoregressive integrated moving average model,ARIMA)对医用耗材消耗量的预测效果。方法:选取某类预冲式冲管注射器2018年7月至2023年6月月度消耗量数据作为样本数据,利用R语言对样本数据进行平稳性检验、差分运算等处理,根据赤池信息准则和贝叶斯信息准则,构建ARIMA模型并确定最优模型。以2023年第三季度相应数据作为验证集进行消耗情况预测,并与实际使用情况进行对比,评价ARIMA模型的预测效果。结果:拟合最优的ARIMA模型为ARIMA(0,1,1)(1,0,0)12,预测数据均在95%置信区间,其平均绝对百分比误差为9.92%,使用Ljung-Box统计量对残差序列进行检验时P>0.05,预测结果较为理想。结论:基于R语言的ARIMA模型对医用耗材消耗量预测效果较好,为医用耗材的需求计划制订、预算、采购、管理等工作提供了参考。展开更多
文章以Web of Science核心合集收录的数字资源长期保存相关文献为数据源,运用R语言科学计量方法,以图谱化的方式呈现数字资源长期保存研究现状,通过主题分析方法归纳总结该领域的研究主题,即数字资源长期保存方法与参与主体、标准规范...文章以Web of Science核心合集收录的数字资源长期保存相关文献为数据源,运用R语言科学计量方法,以图谱化的方式呈现数字资源长期保存研究现状,通过主题分析方法归纳总结该领域的研究主题,即数字资源长期保存方法与参与主体、标准规范与管理、保存对象与内容和保存策略,运用Biblioshiny程序辅助决策模块分析预测我国数字资源长期保存研究将集中在元数据保存、数字资源共享机制和体系构建、数字策展等方向。展开更多
基金the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement of the Catalan government,and to Universitat Ramon Llull for their financial support.The financial support for this work did not influence its outcome.
文摘The current financial education framework has an increasing need to introduce tools that facilitate the application of theoretical models to real-world data and contexts.However,only a limited number of free tools are available for this purpose.Given this lack of tools,the present study provides two approaches to facilitate the implementa-tion of an event study.The first approach consists of a set of MS Excel files based on the Fama–French five-factor model,which allows the application of the event study methodology in a semi-automatic manner.The second approach is an open-source R-programmed tool through which results can be obtained in the context of an event study without the need for programming knowledge.This tool widens the calculus possibilities provided by the first approach and offers the option to apply not only the Fama–French five-factor model but also other models that are common in the finan-cial literature.It is a user-friendly tool that enables reproducibility of the analysis and ensures that the calculations are free of manipulation errors.Both approaches are freely available and ready-to-use.
文摘本文阐述了数据可视化的发展、定义以及作用等基本知识。利用R语言与BDP(Business Data Platform)商业数据平台对中国地震台网近一年3.0级以上地震进行可视化处理。首先进行数据爬取,对数据进行清洗;其次进行R语言的数据可视化;最后利用BDP平台提供的地理信息系统功能,将地震数据与地理空间信息相结合,生成了地震热力图、地震点分布图等可视化效果。实验结果表明,基于R语言与BDP的地震数据可视化方法具有较好的效果和可行性。可视化分析揭示了地震活动的空间分布特征和时序变化规律,为地震预测和防灾工作提供了重要参考。
文摘本文收集了广州地区2003年至2022年的中医药卫生技术人员和医院床位数等数据,采用R语言构建自回归整合移动平均模型(Autoregressive Integrated Moving Average Model,ARIMA)进行中医药卫生资源配置预测研究,分析了广州市中医药卫生资源的情况以及发展趋势,为广州市相关中医药卫生政策制定提供参考依据。
文摘This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and its powerful data management and analysis tools make it suitable for handling complex data analysis tasks.It is also highly customizable,allowing users to create custom functions and packages to meet their specific needs.Additionally,R language provides high reproducibility,making it easy to replicate and verify research results,and it has excellent collaboration capabilities,enabling multiple users to work on the same project simultaneously.These advantages make R language a more suitable choice for complex data analysis tasks,particularly in scientific research and business applications.The findings of this study will help people understand that R is not just a language that can handle more data than Excel and demonstrate that r is essential to the field of data analysis.At the same time,it will also help users and organizations make informed decisions regarding their data analysis needs and software preferences.
文摘目的:探讨基于R语言构建的自回归滑动平均模型(autoregressive integrated moving average model,ARIMA)对医用耗材消耗量的预测效果。方法:选取某类预冲式冲管注射器2018年7月至2023年6月月度消耗量数据作为样本数据,利用R语言对样本数据进行平稳性检验、差分运算等处理,根据赤池信息准则和贝叶斯信息准则,构建ARIMA模型并确定最优模型。以2023年第三季度相应数据作为验证集进行消耗情况预测,并与实际使用情况进行对比,评价ARIMA模型的预测效果。结果:拟合最优的ARIMA模型为ARIMA(0,1,1)(1,0,0)12,预测数据均在95%置信区间,其平均绝对百分比误差为9.92%,使用Ljung-Box统计量对残差序列进行检验时P>0.05,预测结果较为理想。结论:基于R语言的ARIMA模型对医用耗材消耗量预测效果较好,为医用耗材的需求计划制订、预算、采购、管理等工作提供了参考。
文摘文章以Web of Science核心合集收录的数字资源长期保存相关文献为数据源,运用R语言科学计量方法,以图谱化的方式呈现数字资源长期保存研究现状,通过主题分析方法归纳总结该领域的研究主题,即数字资源长期保存方法与参与主体、标准规范与管理、保存对象与内容和保存策略,运用Biblioshiny程序辅助决策模块分析预测我国数字资源长期保存研究将集中在元数据保存、数字资源共享机制和体系构建、数字策展等方向。