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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. | ||
| تاریخ دریافت: 23 اردیبهشت 1400، تاریخ پذیرش: 14 مهر 1400 | ||
| 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 | ||
| مراجع | ||
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