{"title":"Greymodels: A Shiny Package for Grey Forecasting Models in R","authors":"Havisha Jahajeeah, Aslam A. E. F. Saib","doi":"10.1007/s10614-024-10610-8","DOIUrl":null,"url":null,"abstract":"<p>The <span>Greymodels</span> package presents an interactive interface in R for the statistical modelling and forecasting of incomplete or small datasets using grey models. The package, based on the <span>Shiny</span> framework, has been designed to work with univariate and multivariate datasets having different properties and characteristics. The functionality of the package is demonstrated with a few examples and in particular, the user-friendly interface is shown to allow users to easily compare the performance of different models for prediction and among others, visualize graphical plots of predicted values within a user chosen confidence interval. The built-in algorithms in the <span>Greymodels</span> package are extensions or hybrids of the GM<span>\\((1,\\,1)\\)</span> model, and this article covers an overview of the theoretical background of the basic grey model and we also propose a PSO-GM<span>\\((1,\\,1)\\)</span> algorithm in this package.</p>","PeriodicalId":50647,"journal":{"name":"Computational Economics","volume":"2 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s10614-024-10610-8","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The Greymodels package presents an interactive interface in R for the statistical modelling and forecasting of incomplete or small datasets using grey models. The package, based on the Shiny framework, has been designed to work with univariate and multivariate datasets having different properties and characteristics. The functionality of the package is demonstrated with a few examples and in particular, the user-friendly interface is shown to allow users to easily compare the performance of different models for prediction and among others, visualize graphical plots of predicted values within a user chosen confidence interval. The built-in algorithms in the Greymodels package are extensions or hybrids of the GM\((1,\,1)\) model, and this article covers an overview of the theoretical background of the basic grey model and we also propose a PSO-GM\((1,\,1)\) algorithm in this package.
期刊介绍:
Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics. The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing