Sieve bootstrap monitoring persistence change in long memory process
نویسندگان
چکیده
منابع مشابه
Sieve Bootstrap for Time Series Sieve Bootstrap for Time Series
We study a bootstrap method which is based on the method of sieves. A linear process is approximated by a sequence of autoregressive processes of order p = pn, where pn ! 1 ; p n = on as the sample size n ! 1. F or given data, we t h e n estimate such a n A R pn model and generate a bootstrap sample by resampling from the residuals. This sieve bootstrap enjoys a nice nonparametric property. We ...
متن کاملA Sieve Bootstrap approach to constructing Prediction Intervals for Long Memory Time series
This paper is concerned with the construction of bootstrap prediction intervals for autoregressive fractionally integrated movingaverage processes which is a special class of long memory time series. For linear short-range dependent time series, the bootstrap based prediction interval is a good nonparametric alternative to those constructed under parameter assumptions. In the long memory case, ...
متن کاملSieve bootstrap t-tests on long-run average parameters
Panel estimators can provide consistent measures of a long-run average parameter even if the individual regressions are spurious. However, the t-test on this parameter is fraught with problems because the limit distribution of the test statistic is non-standard and rather complicated, particularly in panels with mixed (non-)stationary errors. A sieve bootstrap framework is suggested to approxim...
متن کاملValid Resampling of Higher Order Statistics Using Linear Process Bootstrap and Autoregressive Sieve Bootstrap
Abstract. In this paper we show that the linear process bootstrap (LPB) and the autoregressive sieve bootstrap (AR sieve) fail in general for statistics whose large-sample distribution depends on higher order features of the dependence structure rather than just on autocovariances. We discuss why this is still the case under linearity if it does not come along with causality and invertibility w...
متن کاملMatched-block Bootstrap for Long Memory Processes Matched-block Bootstrap for Long Memory Processes
The block bootstrap for time series consists in randomly resampling blocks of consecutive values of the given data and aligning these blocks into a bootstrap sample The matched block bootstrap Carlstein et al samples blocks dependently attempting to follow each block with one that might realistically follow it in the underlying process to better match the dependence structure of the data Blocks...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistics and Its Interface
سال: 2016
ISSN: 1938-7989,1938-7997
DOI: 10.4310/sii.2016.v9.n1.a4