A proposed conditional method for estimating ARMA(1, 1) model

	A proposed conditional method for estimating ARMA(1, 1) model
International Journal of Nonlinear Analysis and Applications
مقاله 243، دوره 13، شماره 1، خرداد 2022، صفحه 3011-3020 اصل مقاله (328.27 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6032
نویسنده
Lamyaa Mohammed Ali Hameed^*
Department of Statistics, College of Administration and Economic, Baghdad University, Iraq.
چکیده
This paper aims to study the parameters estimation methods of the stationary mixed model (autoregressive-moving average) of low order ARMA (1, 1) regarding to time domain analysis in univariate time series. Using the approximating methods: Back Forecasting (BF), Classical Conditional Maximum Likelihood (CC) and Proposed Conditional Maximum Likelihood(PC). A comparison is done among the three methods by Mean Squared Error (MSE) using several simulation experiments; the obtained results from the empirical analysis indicate that the accuracy of the proposed conditional method is better than the classical conditional method.
کلیدواژه‌ها
ARMA model؛ Estimation؛ Conditional Maximum Likelihood؛ Back Forecasting؛ Sum Squared Error
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