Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

Statistical Methods for Long Term Memory Processes covers the diverse statistical methods
and applications for data with long-range dependence. Presenting material that previously …

It is well known to applied statisticians and scientists that the assumption of independence is
often not valid for real data. In particular, even when all precautions are taken to prevent …

Comprehensive theoretical overview of kernel smoothing methods with motivating examples
Kernel smoothing is a flexible nonparametric curve estimation method that is applicable …

Long-range dependence is often observed in long time series. Correlations decay
approximately like| k| 2H-2, with H ε (0.5, 1), as the lag k tends to infinity. The long-term …

Moving averages in iid variables form one of the most important classes of long memory time
series. The paper reviews various results on the asymptotic distribution of empirical …

Long‐range dependence (LRD) refers to dependence structures that decay slowly with
increasing distance. Mathematically this leads to limit theorems that differ from the short …

We propose a test statistic for goodness of fit in time series with slowly decaying serial
correlations. The asymptotic distribution of the test statistic, originally proposed by Milhoj for …

This paper discusses asymptotic normality of certain classes of M-and R-estimators of the
slope parameter vector in linear regression models with long memory moving average …

Long memory is known to occur in many fields of statistical application. Stationary processes
whose correlations decay asymptotically like‖ k‖ 2H‐2, where k is the lag and Hε (0.5, 1) …