In many instances in empirical spatial analysis, the method of choice is a regression
analysis, whereby a variable of interest (the dependent variable) is related in a linear way to …

The software for spatial econometrics available in the R system for statistical computing is
reviewed. The methods are illustrated in a historical perspective, highlighting the main lines …

A number of problems in probability and statistics can be addressed using the multivariate
normal (Gaussian) distribution. In the one-dimensional case, computing the probability for a …

Although interest in spatial regression models has surged in recent years, a comprehensive,
up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial …

The aim of this book is to investigate the spectral properties of random matrices (RM) when
their dimensions tend to infinity. All classical limiting theorems in statistics are under the …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial
Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects …

Spatial structures of ecological communities may originate either from the dependence of
community structure on environmental variables or/and from community-based processes. In …

In this paper, I give a personal view on the development of the field of spatial econometrics
during the past 30 years. I argue that it has moved from the margins to the mainstream of …

This article provides a survey of the specification and estimation of spatial panel data
models. These models include spatial error autocorrelation, or the specification is extended …