Persistence is an important characteristic of many complex systems in nature, related to how
long the system remains at a certain state before changing to a different one. The study of …

In this chapter we first review the theoretical and empirical work on fractional integration and
cointegration, placing special emphasis on the estimation procedures for fractionally …

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

We present a new technique for isolating climate signals in time series with a characteristic
'red'noise background which arises from temporal persistence. This background is estimated …

This study uses an extensive dataset of monthly surface air temperature (SAT) records
(including previously unutilized) from high-latitude (> 60° N) meteorological land stations …

Trends in flood and low flows in the US were evaluated using a regional average Kendall's
S trend test at two spatial scales and over two timeframes. Field significance was assessed …

The problem of estimating underlying trends in time series data arises in a variety of
disciplines. In this paper we propose a variation on Hodrick–Prescott (HP) filtering, a widely …

Trends in Canadian temperature and precipitation during the 20th century are analyzed
using recently updated and adjusted station data. Six elements, maximum, minimum and …

We take a simple time series approach to modeling and forecasting daily average
temperature in US cities, and we inquire systematically as to whether it may prove useful …

The change in the mean temperature in Finland is investigated with a dynamic linear model
in order to define the sign and the magnitude of the trend in the temperature time series …