Hybridization of long short-term memory neural network in fractional time series modeling of inflation [PDF]
Frontiers in Big Data, 2023 Inflation is capable of significantly impacting monetary policy, thereby emphasizing the need for accurate forecasts to guide decisions aimed at stabilizing inflation rates.
Erman Arif +4 more
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Considerations for Applying Entropy Methods to Temporally Correlated Stochastic Datasets [PDF]
Entropy, 2023 The goal of this paper is to highlight considerations and provide recommendations for analytical issues that arise when applying entropy methods, specifically Sample Entropy (SampEn), to temporally correlated stochastic datasets, which are representative
Joshua Liddy, Michael Busa
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IDENTIFICACIÓN DE MODELOS ARFIMA
Revista de la Facultad de Ciencias, 2016 Desde la introducción de los modelos fraccionalmente integrados ARFIMA para series de tiempo con memoria larga, ha surgido un gran interés en el estudio de sus propiedades y áreas de aplicación.
Elkin Castaño-Vëlez
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Evaluating the long-term impact of COVID-19-associated public health interventions on zoonotic and vector-borne diseases in China: an interrupted time series analysis [PDF]
Journal of Translational MedicineBackground The long-term impact of COVID-19-associated public health interventions on zoonotic and vector-borne infectious diseases (ZVBs) remains uncertain.
Yongbin Wang +8 more
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التنبؤ باستخدام نموذج الانحدار الذاتي والمتوسطات المتحركة التكاملية الكسرية ARFIMA (p, d, q) : دراسة تطبيقية [PDF]
المجلة العلمية للدراسات والبحوث المالية والتجارية, 2023 تم في هذا البحث دراسة وعرض خطوات تحليل السلاسل الزمنية باستخدام نموذج الانحدار الذاتي والمتوسطات المتحركة التكاملية الكسرية "نموذج السلاسل الزمنية ذات الذاكرة الطويلة" ARFIMA (p, d, q).
أمال عبد الغني +1 more
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ARFIMA Model for Short Term Forecasting of New Death Cases COVID-19 [PDF]
E3S Web of Conferences, 2020 COVID-19 is an infectious disease that can spread from one person to another and has a high potential for death. The infection of COVID-19 is spreading massive and fast that causes the extreme fluctuating data spread and long memory effects.
Kartikasari Puspita +2 more
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Frontiers in Applied Mathematics and Statistics, 2022 IntroductionThe price of crude oil as an essential commodity in the world economy shows a pattern and identifies the component factors that influence it in the short and long term.
Dodi Devianto +4 more
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BOOTSTRAP ASSISTED SPECIFICATION TESTS FOR THE ARFIMA MODEL [PDF]
Econometric Theory, 2011 This paper proposes bootstrap assisted specification tests for the autoregressive fractionally integrated moving average model based on the BartlettTp-process with estimated parameters whose limiting distribution under the null depends on the estimated model and the estimation method employed.
Delgado, Miguel A. +2 more
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Fractional differencing in stock market price and online presence of global tourist corporations [PDF]
Journal of Economics Finance and Administrative Science, 2019 Purpose - This work aims to explore the behavior of stock market prices according to the autoregressive fractional differencing integrated moving average model.
Francisco Flores-Muñoz +2 more
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MODELLING FOR THE WAVELET COEFFICIENTS OF ARFIMA PROCESSES [PDF]
Journal of Time Series Analysis, 2014 AbstractWe consider a model for the discrete nonboundary wavelet coefficients of autoregressive fractionally integrated moving average (ARFIMA) processes in each scale. Because the utility of the wavelet transform for the long‐range dependent processes, which many authors have explained in semi‐parametrical literature, is approximating the transformed ...
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