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Indirect and Direct Bayesian Techniques to Identify the Orders of Vector ARMA Processes [PDF]
The Egyptian Statistical Journal, 2018 This article develops two bayesian techniques to identify the orders of vector mixed autogressive moving average processes namely the indirect and direct techniques. The proposed indirect technique approximates the joint posterior
Samir M. Shaarawy +2 more
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Estimation for heavy tailed moving average process [PDF]
Kybernetika, 2018 Summary: In this paper, we propose two estimators for a heavy tailed MA(1) process. The first is a semi parametric estimator designed for MA(1) driven by positive-value stable variables innovations. We study its asymptotic normality and finite sample performance.
Hakim Ouadjed, Tawfiq Fawzi Mami
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Mathematics, 2022 In addition to monitoring the Poisson mean rate with step shifts, increasing attention has been given to monitoring Poisson processes subject to linear trends.
Honghao Zhao +3 more
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Moving averages of ergodic processes
Metrika, 1977 A necessary and sufficient condition for the almost everywhere convergence of the “moving” ergodic averages\((\Phi (n))^{ - 1} \mathop \Sigma \limits_{i = n - \Phi (n) + 1}^n x_E (T^i x)\) is given. The result is then generalized to ergodic flows, and finally constrasted with earlier results ofPfaffelhuber andJain.
Junco, A. del, Steele, J.M.
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Connection Science, 2022 The mixed control chart is proposed to improve detection performance with fewer process shifts. In this study, we proposed the modified exponentially weighted moving average - moving average control chart (MMEM), a new mixed control chart for observing the changes in the process mean. Average run length, standard deviation of run length, and median run
Khanittha Talordphop +2 more
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Continuous Time Autoregressive Moving Average Processes Driven by Semi-Levy Process
پژوهشهای ریاضی, 2020 Introduction A flexible and tractable class of linear models is Autoregressive moving average (ARMA) process that are in effect of discrete noises. The continuous time ARMA (CARMA) processes have wide applications in many data modeling where are more ...
Navideh Modarresi +2 more
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Linear Stochastic Models in Discrete and Continuous Time
Econometrics, 2020 The econometric data to which autoregressive moving-average models are commonly applied are liable to contain elements from a limited range of frequencies. If the data do not cover the full Nyquist frequency range of [0,π] radians, then severe biases can
D. Stephen G. Pollock
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Detection of Mutual Exciting Structure in Stock Price Trend Dynamics
Entropy, 2021 We investigated a comprehensive analysis of the mutual exciting mechanism for the dynamic of stock price trends. A multi-dimensional Hawkes-model-based approach was proposed to capture the mutual exciting activities, which take the form of point ...
Shangzhe Li +4 more
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Modeling process asymmetries with Laplace moving average [PDF]
Computational Statistics & Data Analysis, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nicolas Raillard +2 more
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A Bayesian nonlinearity test for threshold moving average models
, 2010 We propose a Bayesian test for nonlinearity of threshold moving average (TMA) models. First, we obtain the marginal posterior densities of all parameters, including the threshold and delay, of the TMA model using Gibbs sampler with the Metropolis ...
Zhiqiang Zhang +7 more
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