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jeasiq-1824
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous variables (GARCHX) are applied to analyze and capture the volatility that occurs in the conditional variance of a linear model. Since time series observations rarely have linear or nonlinear components in nature or usually included together. Therefore, the main purpose of this paper is to employ the hybrid model technique according to Zhang methodology for hybrid models to combine the linear forecasts of the best linear model of ARMAX models and the nonlinear forecasts of the best nonlinear models of (ARCH, GARCH & GARCHX) models and thus increase the efficiency and accuracy of performance forecasting future values of the time series.

This paper is concerned with the modeling and building of the hybrid models (ARMAX-GARCH) and (ARMAX-GARCHX), assuming three different random error distributions: Gaussian distribution, Student-t distribution, as well as the general error distribution and the last two distributions were applied for the purpose of capturing the characteristics of heavy tail distributions which have a Leptokurtic characteristic compared to the normal distribution. This research adopted a modern methodology in estimating the parameters of the hybrid model namely the (two-step procedure) methodology. In the first stage, the parameters of the linear model were estimated using three different methods: The Ordinary Least Squares method (OLS), the Recursive Least Square Method with Exponential Forgetting Factor (RLS-EF), and the Recursive Prediction Error Method (RPM). In the second stage, the parameters of the nonlinear model were estimated using the MLE method and employing the numerical improvement algorithm (BHHH algorithm).

 

 

 

The hybrid models have been applied for modeling the relationship between the exogenous time series represented by the exchange rate and the endogenous time series represented by the unemployment rate in the USA for the period from (January 2000 to December 2017 i.e. 216 observations), and also the out-of-sample forecasts of unemployment rate in the last twelve values of (2018). The forecasting performance of the hybrid models and the competing individual model was also evaluated using the loss function accuracy measures (MAPE), (MAE), and the robust (Q-LIKE). Based on statistical measurements, the results showed the hybrid models improved the accuracy and efficiency of the single model. () hybrid model error whose conditional variance follows a GED distribution is the optimal model in modeling the bivariate time series data under study and more efficient in the forecasting process compared with the individual model and the hybrid model. This is due to having the lowest values for accuracy measures. Different software packages (MATLAB (2018a), SAS 9.1, R 3.5.2 and EViews 9) were used to analyze the data under consideration.

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Publication Date
Sat Jun 01 2013
Journal Name
International Journal Of Astronomy And Astrophysics
Distances Scale Determination for a Planetary Nebula in Galagtic Bulge
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Publication Date
Sun Jan 01 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
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A Parallel Adaptive Genetic Algorithm for Job Shop Scheduling Problem
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A new vision for the classic in contemporary fashion designResearch
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Major Drivers for COVID-19 Vaccine Acceptance: A Scoping Review
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Psychological damage is one of the damages that can be compensated under the fault of negligence in the framework of English law, where the latter intends to include an enumeration of civil errors on the basis of which liability can be determined, and aims under each of these errors to protect a specific interest (for example, defamation protects Among the damage to reputation and inconvenience are the rights contained on the land), and the same is true for the rest of the other errors. Compensation for psychological damage resulting from negligence has raised problems in cases where the psychological injury is "pure", that is, those that are not accompanied by a physical injury, which required subjecting them to special requirements by the

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Sun Mar 04 2018
Journal Name
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Publication Date
Fri Dec 23 2022
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Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
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Synthetic anti-TB drugs are being used to treat tuberculosis (TB) as they are effective, however, they are accompanied by many side effects. The disease has remained largely uncured till date. The use of plant extracts or phytochemicals along with the anti-TB drugs is a very attractive strategy to make the treatment more effective as phytochemicals have no side-effects, are much less toxic than synthetic anti-TB drugs, are safe to use and most importantly, do not produce resistant strains as opposed to synthetic anti-TB drugs. Approximately 420,000 plant species have been identified globally and among them only a few have been explored for their therapeutic potential. Traditional medicine in different parts of the world has employed crud

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