A BAYESIAN APPROACH FOR ESTIMATING AUTOREGRESSIVE MOVING AVERAGE MODELS
| المصدر: | مجلة البحوث التجارية |
|---|---|
| الناشر: | جامعة الزقازيق - كلية التجارة |
| المؤلف الرئيسي: | Hussein, Hassan M. A. (Author) |
| المجلد/العدد: | مج30, ع2 |
| محكمة: | نعم |
| الدولة: |
مصر |
| التاريخ الميلادي: |
2008
|
| الشهر: | يوليو |
| الصفحات: | 29 - 51 |
| رقم MD: | 665250 |
| نوع المحتوى: | بحوث ومقالات |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| رابط المحتوى: |
عدد مرات التحميل
4
| المستخلص: |
A Bayesian method for estimating autoregressive-moving average (ARMA) models is proposed. The proposed methodology is based on replacing lagged errors of the original ARMA model with appropriately lagged residuals from a long auto regression .Bayes estimators have been developed under non-informative and natural conjugate priors. Moreover, the estimation of the parameters for the ARMA representation can be obtained by using a non-Bayesian method, namely the three- stage least squares (3SLS) method. These methods are compared using simulated and real data. A numerical comparison between Bayesian and non-Bayesian will be carried out .It has been seen that the obtained estimators not available in a compact form, although they can be easily evaluated numerically. Moreover, the proposed method (Bayesian procedure) produce estimates with greater precision (smaller MSE) than that for the 3SLS procedure. |
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