Tests of stationarity are routinely applied to highly autocorrelated time series. Following Kwiatkowski et al. (J. Econom. 54 (1992) 159), standard stationarity tests employ a rescaling by an estimator of the long-run variance of the (potentially) stationary series. This paper analytically investigates the size and power properties of such tests when the series are strongly autocorrelated in a ...

How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species...

The statistical properties of the energy landscape of the low autocorrelated binary string problem (LABSP) are studied numerically and compared with those of several classic disordered models. Using two global measures of landscape structure which have been introduced in the Simulated Annealing literature, namely, depth and difficulty, we find that the landscape of LABSP, except perhaps for a v...

Many theories in political science predict the spatial clustering of similar behaviors among neighboring units of observation. This spatial autocorrelation poses implications for both inference and modeling that are distinct from the more familiar serial dependence in time series analysis. In this paper, I examine how political scientists can diagnose and model the spatial dependence that is pr...

Ecological communities are open to the immigration of individuals and are variable through time. In open habitats immigration may permit populations of a species to persist locally even though local biotic and abiotic processes tend to exclude such "sink" populations. A general model for a sink population reveals that autocorrelated environmental variation can dramatically inflate local abundan...

When trying to determine which of two causes produces a more desirable outcome, if the outcome is autocorrelated (goes through higher and lower periods) it is critical to switch back and forth between the causes. If one first tries Cause 1, and then tries Cause 2, it is likely that an autocorrelated outcome would appear to change with the second cause even though it is merely undergoing normal ...

Information security issues are characterized with interdependence. Particularly, cyber criminals can easily cross national boundaries and exploit jurisdictional limitations between countries. Thus, whether cyber attacks are spatially autocorrelated is a strategic issue for government authorities and a tactic issue for insurance companies. Through an empirical study of cyber attacks across 62 c...

In many circumstances, the quality of a process or product is best characterized by a given mathematical function between a response variable and one or more explanatory variables that is typically referred to as profile. There are some investigations to monitor autocorrelated linear and nonlinear profiles in recent years. In the present paper, we use the linear mixed models to account autocorr...

The distribution and extinction patterns within a northern metapopulation of the pool frog (Rana lessonae) were analyzed with reference to metapopulation theory. Occupied ponds were permanent and differed from unoccupied ones in terms of higher water temperature during May-June and a closer proximity to neighboring pool-frog localities. but local climate was not spatially autocorrelated. Two ty...

In this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against th...