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17 results for “multivariate time models”
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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 · 16,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractTime Series Analysis of Rainfall and Temperature Interactions in Coastal CatchmentsGurudeo Anand Tularam, Mahbub IlaheeProblem statement: As a result of climate change more work is now being done on climate indices such as SOI, rainfall, temperature and so on. The research concerning rainfall and temperature variations in coastal tropical and subtropical catchments as noted by the dated references in this study shows a lack of attention. The authors examined long term data from coastal … …Journal of Mathematics and Statistics, Vol. 6, Issue 3 · 30 Sep 2010 · 15,823 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Numerical Computation of Rational Structures and Asymptotic Standard Deviations in Causal Time Series DataConcepción González-Concepción, María Candelaria Gil-Fariña, Celina Pestano-GabinoProblem statement: The specific properties of data series are of primary importance in several sciences. In the field of time series analysis, several researchers have considered the rational approximation theory, particularly the Padé Approximation and Orthogonal Polynomials. Approach: In this study, an approach for the statistical significance of two numerical methods, the r-s and q-d algorithm, was proposed which made … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 7,049 accessesView PDFCite
Research ArticleOpen accessIn the abstractVAR-models for Predicting BiodiversityTonio D. Bettista, S. A. Gattone, Mariagrzia GranturcoThe aim of this work is to introduce a methodology for monitoring diversity of a biological population by using the tool of diversity profiles. In particular, we develop a theory for studying the diversity profile along the temporal axis. We propose forecasting techniques for diversity profile by using the VAR model on multivariate time series of abundance vector and ARMA … …Journal of Mathematics and Statistics, Vol. 1, Issue 4 · 31 Dec 2005 · 6,175 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,074 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordPrediction on Land Market Value Based on the Real Estate Market in USALei WangThe Land Market Value, defined as the total value of land price and quantity data are derived from data on housing values, is an important factor in the estimation of structure costs using price indexes for housing and construction costs. In this study, we gather and analyze 34 years' national data on past and present real estate transaction. According to … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 23 May 2017 · 7,555 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordStatistical Bayesian Learning for Automatic Arabic Text CategorizationBassam Al-Salemi, Mohd. Juzaiddin Ab AzizProblem statement: The rapid increasing of online Arabic documents necessitated applying Text Categorization techniques that are commonly used for English language to categorize them automatically. The complex morphology of Arabic language and its large vocabulary size make applying these techniques directly difficult and costly in time and effort. Approach: We have investigated Bayesian learning models in order to enhance Arabic … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,399 accessesView PDFCite