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On the Empirical Spectral Distribution of Lag-Covariance Matrix in Singular Spectrum Analysis | ||
| Caspian Journal of Mathematical Sciences | ||
| مقاله 13، دوره 10، شماره 2، اسفند 2021، صفحه 280-288 اصل مقاله (302.27 K) | ||
| نوع مقاله: Research Articles | ||
| شناسه دیجیتال (DOI): 10.22080/cjms.2021.18838.1507 | ||
| نویسندگان | ||
| Hormoz Rahmatan* 1؛ Mahdi Kalantari2 | ||
| 1Department of Mathematics, Faculty of Science, Payame Noor University, P.O.Box 19395-3697, Tehran, Iran | ||
| 2Department of Statistics,, Faculty of Science, Payame Noor University, P.O.Box 19395-4697, Tehran, Iran | ||
| تاریخ دریافت: 29 اردیبهشت 1399، تاریخ بازنگری: 19 بهمن 1399، تاریخ پذیرش: 20 بهمن 1399 | ||
| چکیده | ||
| Singular Spectrum Analysis (SSA) is a non-parametric and rapidly developing method of time series analysis. Recently, this technique receives much attention in a variety of fields. In SSA, a special matrix that is called lag-covariance matrix plays a pivotal role in analyzing stationary time series. The objective of this paper is to examine whether the Empirical Spectral Distribution (ESD) of lag-covariance matrix converges to Marˇcenko{Pastur distribution or not. Such limiting distribution can help us to provide more reliable statistical inference when encountering with high-dimensional data. Moreover, a simulation study is performed and some tools of Random Matrix Theory (RMT) are used. | ||
| کلیدواژه‌ها | ||
| Singular Spectrum Analysis؛ Random Matrix Theory؛ Empirical Spectral Distribution؛ MarˇcenkoPastur Distribution؛ Lag-Covariance Matrix | ||
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آمار تعداد مشاهده مقاله: 357 تعداد دریافت فایل اصل مقاله: 284 |
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