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16 articles for “multivariate time models”
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Research ArticleOpen accessEvery word in the titleAdvanced Multivariate Time Series Forecasting ModelsMiss Lei WangIn this study, the focus is to collect and summarize various advanced forecasting models for multivariate time series dataset. We have discussed about the inherent forecasting strengths and weaknesses related to these time series modelings. Also, the main section deal with the experience of using such data in econometric analysis. Besides, the implementation of SAS and R softwares improve the … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 21 Dec 2018 · 7,323 accessesView PDFCite
Research ArticleOpen accessIn the keywordsMultivariate Modelling of the Canary Islands Banana Output. The Role of Farmer Income ExpectationConcepción González Concepción, María Candelaria Gil-Fariña, Celina Pestano-GabinoThe EU is the world‘s largest importer of bananas and the only major managed market in the international banana trade. Spain is the main banana producer within the European Union (EU), followed by France and Portugal. In all these countries the fruit is grown in overseas islands situated in tropical or sub-tropical areas and bananas are a pillar of the … …Journal of Social Sciences, Vol. 4, Issue 2 · 30 Jun 2008 · 7,769 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting CO2 Emissions Using Multivariate Regression: Assessing the Impact of Pandemics and Industrial RevolutionsYoussef Mekki, Chouaib Moujahdi, Noureddine Assad, Aziz DahbiThis paper explores the prediction of CO2 emissions usingMultivariate Regression models, incorporating the influence of significanthistorical events such as pandemics and industrial revolutions. Whileexisting research primarily focuses on carbon emissions alone in forecastingmodels, this study emphasizes the importance of incorporating multiplefactors for a comprehensive understanding of CO2 dynamics. Beyondemissions, factors such as socioeconomic indicators, industrial activities,environmental policies, and historical events … …Journal of Computer Science, Vol. 21, Issue 7 · 23 Jul 2025 · 3,432 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Learning Framework for Classifying and Evaluating Yoga ExercisesMehar Latif Malik, Arun KhoslaYoga is a type of physical activity that combines physical postures with breathing techniques. Cardiovascular disease is the leading cause of illness and mortality. Yoga's potential involvement in cardiac recovery can be incorporated into cardiovascular rehabilitation. Classifying and evaluating yoga exercises using a deep learning framework plays a significant role in postoperative recovery. Home based rehabilitation often suffers from a … …Journal of Computer Science, Vol. 19, Issue 2 · 30 Jan 2023 · 6,098 accessesView PDFCite
Case ReportOpen accessIn the abstractEvaluation of Seasonal Autoregressive Integrated Moving Average Models for River Flow ForecastingKassahun Birhanu Tadesse, Megersa Olumana Dinka, Tena Alamirew, Semu Ayalew MogesReservoir operation policies cannot be functional in instant decision making without forecasting the future reservoir inflows. For forecasting inflows into reservoirs with only hydrological data is available like Koga irrigation dam, multivariate forecasting models cannot be used to generate accurate river flow information. As a result, an evaluation of univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) models was done for … …American Journal of Environmental Sciences, Vol. 13, Issue 5 · 28 Sep 2017 · 7,891 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,762 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing Convergence of the Markov Chain Monte Carlo Method in Multivariate CaseDenismar Alves Nogueira, Thelma Safadi, Daniel Furtado Ferreira, Eric Batista FerreiraThe formal convergence diagnosis of the Markov Chain Monte Carlo (MCMC) is made using univariate and multivariate criteria. In 1998, a multivariate extension of the univariate criterion of multiple sequences was proposed. However, due to some problems of that multivariate criterion, an alternative form of calculation was proposed in addition to the two new alternatives for multivariate convergence criteria. In … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 8 Jan 2013 · 7,021 accessesView PDFCite
Research ArticleOpen accessIn the abstractSex, Health Behaviors and Social Support: Functional Decline among Older DiabeticsEmily Joy NicklettProblem statement: Men and women experience pronounced differences in functional decline as they age. The mechanisms behind these differences remain unclear, particularly among chronically ill populations. Drawing on the theory of the disablement process, this research examines sex differences in functional decline, focusing on two mechanisms suggested by the literature to partially mediate these disparities: health behaviors and social support. … …Current Research in Medicine, Vol. 3, Issue 2 · 19 May 2012 · 8,048 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving the Performance of Multivariate Bernoulli Model based Documents Clustering Algorithms using Transformation TechniquesPerumal Pitchandi, Nedunchezhian RajuProblem statement: Document clustering is the most important areas of data mining since they are very much and currently the subject of significant global research since such areas strengthen the enterprises of web intelligence, web mining, web search engine design and so forth. Generative models based on the multivariate Bernoulli and multinomial distributions have been widely used for text classification. … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,284 accessesView PDFCite
Research ArticleOpen accessIn the abstractInvestigation of Socially Responsible Investment Markets (SRI) Using Dynamic Conditional Correlation (DCC) Method: Implications for DiversificationGurudeo Anand Tularam, Eduardo Roca, Victor Siew Howe WongProblem statement: Over the last ten years there has been a phenomenal growth in the amount of funds placed in SRI globally estimated to be around US$6.5 trillion while around US$55 billion in the Australian market. Accurate knowledge of correlation of the Australian SRI market with other SRI markets overseas is crucially important for Australian (SRI) investors for international portfolio … …Journal of Mathematics and Statistics, Vol. 6, Issue 4 · 4 Nov 2010 · 16,240 accessesView PDFCite