Results 21 to 30 of about 10,065 (268)
PLoS ONE, 2022 SVR-ARMA-GARCH models provide flexible model fitting and good predictive powers for nonlinear heteroscedastic time series datasets. In this study, we explore the change point detection problem in the SVR-ARMA-GARCH model using the residual-based CUSUM ...
HsinKai Wang +3 more
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Estimation of the parameters of symmetric stable ARMA and ARMA–GARCH models [PDF]
Journal of Applied Statistics, 2021 In this article, we first propose the modified Hannan-Rissanen Method for estimating the parameters of the autoregressive moving average (ARMA) process with symmetric stable noise and symmetric stable generalized autoregressive conditional heteroskedastic (GARCH) noise.
Sathe, Aastha M., Upadhye, N. S.
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Estimation of ARMA Model Order via Artificial Neural Network for Modeling Physiological Systems
IEEE Access, 2020 Model order estimation is the most important but challenging step for system identification using an autoregressive moving average (ARMA) model. In this paper, we propose an artificial neural network (ANN) structure to estimate the best model order for ...
Md-Billal Hossain +2 more
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Fully Bayesian Analysis of Bivariate Arma Models [PDF]
The Egyptian Statistical Journal, 1991 This paper proposes a convenient way to do a complete Bayesian analysis of bivariate time series generated by auto-regressive moving average models. The identification, estimation, diagnostic checking, and forecasting phases of time series analysis is ...
Samir Shaarawy
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Implied Volatility Prediction Based on Different Term Structures: An Empirical Study of the SSE 50 ETF Options Market from High-Frequency Data [PDF]
E3S Web of Conferences, 2021 This article focuses on the implied volatility forecast of the SSE 50 ETF options market from June 1, 2017, to August 30, 2019, and constructs AR (1) model and ARMA-GARCH model based on liquidity characteristics to compare and analyze the prediction ...
Yang Wenqi, Ma Jingkun
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The Scientific World Journal, 2014 The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes.
Melike Bildirici, Özgür Ersin
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The Annals of Statistics, 1975 In estimating a vector model, $\Sigma B(j)x(n-j)=\Sigma A(j)\epsilon(n-j), A(0)=I_r, E(\epsilon(m)\epsilon(n)')=\delta_{mn}K$ it is suggested that attention be confined to cases where $g(z) =\Sigma A(j)z^j, h(z)=\Sigma B(j)z^j$ have determinants with no zeroes inside the unit circle and have $I_r$ as greatest common left divisor and where $\1brack A(p)\
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Prediction and Analysis of Meteorological Drought Based on Time Series(Case Study: SALMAS Watershed) [PDF]
محیط زیست و مهندسی آب, 2016 Time series analyses is a base method for more decisions about hydrological process and water operation. In Iran, drought is a continues and normal condition happening frequently and can be predicted by statistical and mathematical methods and models. In
Motaleb Byzedi +2 more
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Clustered Hybrid Wind Power Prediction Model Based on ARMA, PSO-SVM, and Clustering Methods
IEEE Access, 2020 Wind power prediction is the key technology to the safe dispatch and stable operation of power system with large-scale integration of wind power. In this work, based on the historical data of wind power, wind speed and temperature, the autoregressive ...
Yurong Wang, Dongchuan Wang, Yi Tang
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Heliyon, 2023 The article focuses on analyzing the robustness of Auto Regressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) methods in unemployment rate estimation. In this context, a stochastic trend in the unemployment rate was determined
Dilek Surekci Yamacli, Serhan Yamacli
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