کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
13470747 1846326 2019 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Frequency domain bootstrap for ratio statistics under long-range dependence
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آمار و احتمال
پیش نمایش صفحه اول مقاله
Frequency domain bootstrap for ratio statistics under long-range dependence
چکیده انگلیسی
A frequency domain bootstrap (FDB) is a common technique to apply Efron's independent and identically distributed resampling technique (Efron, 1979) to periodogram ordinates - especially normalized periodogram ordinates - by using spectral density estimates. The FDB method is applicable to several classes of statistics, such as estimators of the normalized spectral mean, the autocorrelation (but not autocovariance), the normalized spectral density function, and Whittle parameters. While this FDB method has been extensively studied with respect to short-range dependent time processes, there is a dearth of research on its use with long-range dependent time processes. Therefore, we propose an FDB methodology for ratio statistics under long-range dependence, using semi- and nonparametric spectral density estimates as a normalizing factor. It is shown that the FDB approximation allows for valid distribution estimation for a broad class of stationary, long-range (or short-range) dependent linear processes, without any stringent assumptions on the distribution of the underlying process. The results of a large simulation study show that the FDB approximation using a semi- or nonparametric spectral density estimator is often robust for various values of a long-memory parameter reflecting magnitude of dependence. We apply the proposed procedure to two data examples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of the Korean Statistical Society - Volume 48, Issue 4, December 2019, Pages 547-560
نویسندگان
, ,