Consider the fractional ARIMA time series with innovations that have innnite variance. This is a nite parameter model which exhibits both long-range dependence (long memory) and high variability. We prove the consistency of an estimator of the unknown parameters which is based on the periodogram and derive its asymptotic distribution. This shows that the results of Mikosch, Gadrich, Kl uppelber...

Nonstationary ARIMA processes and nearly nonstationary ARMA processes, such as autoregressive processes having a root of the AR polynomial close to the unit circle, have sample autocovariance and spectral properties that are, in practice, almost indistinguishable from those of a stationary longmemory process, such as a Fractionally Integrated ARMA (ARFIMA) process. Because of this, model misspe...

Measurements of high-speed network traffic have shown that traffic data exhibits a high degree of self-similarity. Traditional traffic models such as AR and ARMA are not able to capture this long-range-dependence making them ineffective for the traffic prediction task. In this paper, we apply the fractional ARIMA (F-ARIMA) model to predict one-step-ahead traffic value at different time scales. ...

این پژوهش با الهام گرفتن از نتایج یک طرح مطالعاتی کاربردی، رویکرد سلسله­‌مراتبی جهت پیگیری فرایند توسعه تأمین‌کنندگان و حمایت تصمیمات موجود در هر مراحل آن ارائه‌ می‌کند. ابتدا، زمینه‌های تأمین نیازمند سپس واجد شرایط هریک زمینه‌ها به کمک تصمیم‌گیری چندشاخصه بهترین-بدترین مشخص می‌گردند. معیارهای شناسایی نیز مرور مطالعات پیشین بهره‌گیری نظرات خبرگان حوزه‌ی خرید استخراج‌شده‌اند. درنهایت، مدل ریاضی ...

This report surveys time series methods that have been used and can be applied in predicting end-to-end delay of the Internet. ARIMA scheme and state-space approach are discussed and compared. Although state-space approach has the advantages in structure and computation, ARIMA modeling is still useful in identifying systems due to the complexity and uncertainty of the Internet. A practical exam...