To seek stochastic analogies in key processes related to the hydrological cycle, an extended
collection of several billions of data values from hundred thousands of worldwide stations is …

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 …

This paper provides a survey and review of the major econometric work on long memory
processes, fractional integration, and their applications in economics and finance. Some of …

Let X t, t≤ T be a sample of discrete or continuous data that is randomly generated and
takes values in r-dimensional Euclidean space. The distribution of X t depends on a …

We study problems of semiparametric statistical inference connected with long-memory
covariance stationary time series, having spectrum which varies regularly at the origin …

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 …

This paper provides a bibliographical guide to researchers and tra c engineers who are
interested in self-similar tra c modeling and analysis. It lists some of the most recent network …

Since Hurst [1951] detected the presence of long‐term persistence in hydrologic data, new
estimation methods and long‐memory models have been developed. The lack of flexibility in …

A seasonal fractional autoregressive integrated moving average (ARIMA) model is
introduced, with both short‐and long‐term persistent periodic components. The estimation of …