recordings of ambient noise or microtremors are increasingly used to find valuable information on soil in one dimension at a given site. ambient vibrations, which are assumed to be mainly composed of surface waves, can be used to determine the surface wave dispersion curve in order to retrieve shear wave velocity profile. in this regard, microtremors are usually recorded simultaneously in an ar...

This paper examines the role of spatial effects in ecological inference. Both formally and through simulation experiments, we consider the problems associated with ecological inference and cross-level inference methods in the presence of increasing degrees of spatial autocorrelation. Past assessments of spatial autocorrelation in aggregate data analysis focused on unidimensional, one-directiona...

In many spatial data applications, the events at a location are highly influenced by the events at neighboring locations. In fact, this natural inclination of a variable to exhibit similar values as a function of distance between the spatial locations at which it is being measured is known as spatial dependence. Spatial autocorrelation is used to measure this spatial dependence. If the variable...

Most spatial data in GIS are not independent, they have high autocorrelation. For example, temperatures of nearby locations are often related. Most of the spatial association rule mining algorithms derived from the attribute association rule mining algorithms which assume that spatial data is independent. In these situations, the rules or knowledge derived from spatial mining will be wrong. It ...

This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed in this paper, the (quasi) maximum likelihood estimator may not be computationally feasible in m...

Spatial and geographic constructs have been incorporated into strategy research since its inception. Yet, strategy researchers have been slow to take advantage of methods designed specifically for these variables. This is despite the fact that spatial methods can be used to identify and remediate spatial autocorrelation—eliminating a potentially important source of bias in empirical results—and...

This paper is concerned with the estimation of the autoregressive parameter in a widely considered spatial autocorrelation model. The typical estimator for this parameter considered in the literature is the (quasi) maximum likelihood estimator corresponding to a normal density. However, as discussed in the paper, the (quasi) maximum likelihood estimator may not be computationally feasible in ma...

This paper introduces the spatial panel autocorrelation model, utilizes C-D production functions, constructs the spatial econometric model and finally studies the spatial correlativity between provincial economic growth and logistics. By using the spatial package of Matlab software, it verifies the possibility if there is the remarkable autocorrelation of the Chinese provincial economic growth ...