کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8919460 | 1642889 | 2018 | 49 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Change point detection in heteroscedastic time series
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
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چکیده انگلیسی
Many time series exhibit changes both in level and in variability. Generally, it is more important to detect a change in the level, and changing or smoothly evolving variability can confound existing tests. A framework for testing for shifts in the level of a series which accommodates the possibility of changing variability is developed. The resulting tests are robust both to heteroskedasticity and serial dependence. They rely on a new functional central limit theorem for dependent random variables whose variance can change or trend in a substantial way. This new result is of independent interest as it can be applied in many inferential contexts applicable to time series. Its application to change point tests relies on a new approach which utilizes Karhunen-Loéve expansions of the limit Gaussian processes. After presenting the theory in the most commonly encountered setting of the detection of a change point in the mean, it is shown how it can be extended to linear and nonlinear regression. Finite sample performance is examined by means of a simulation study and an application to yields on US treasury bonds.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Econometrics and Statistics - Volume 7, July 2018, Pages 63-88
Journal: Econometrics and Statistics - Volume 7, July 2018, Pages 63-88
نویسندگان
Tomasz Górecki, Lajos Horváth, Piotr Kokoszka,