| تعداد نشریات | 24 |
| تعداد شمارهها | 859 |
| تعداد مقالات | 7,631 |
| تعداد مشاهده مقاله | 13,515,249 |
| تعداد دریافت فایل اصل مقاله | 11,637,833 |
Strongly Harmonizable ARMA SalphaS Models | ||
| Iranian Journal of Science | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 03 بهمن 1394 | ||
| نوع مقاله: Regular Paper | ||
| شناسه دیجیتال (DOI): 10.22099/ijsts.2016.3540 | ||
| نویسنده | ||
| Bahram Tarami* | ||
| Dept. of Stat., College of Sciences, Shiraz Univ., Shiraz, Iran | ||
| چکیده | ||
| It is well known that no strongly harmonizable S S process assumes classical ARMA representation with respect to a SalphaS noise sequence with independent values. In this article we introduce certain strongly harmonizable ARMA SalphaS models, in which the noise sequences have orthogonal values in certain Hilbert spaces. Our study on strongly harmonizable ARMA SalphaS models involves parameter estimation, simulation, moving average representation, regularity and prediction. We generate the corresponding noise series, that appear to be challenging and interesting. | ||
| کلیدواژهها | ||
| strongly harmonizable processes؛ ARMA models؛ regularity؛ moving average representation؛ prediction؛ Simulation | ||
|
آمار تعداد مشاهده مقاله: 1,464 |
||