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 …

With increasing accessibility to geographic information systems (GIS) software, statisticians
and data analysts routinely encounter scientific data sets with geocoded locations. This has …

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 …

Among the many uses of hierarchical modeling, their application to the statistical analysis of
spatial and spatio-temporal data from areas such as epidemiology And environmental …

Conventional geostatistical methodology solves the problem of predicting the realized value
of a linear functional of a Gaussian spatial stochastic process S (x) based on observations …

Spatial scan statistics with Bernoulli and Poisson models are commonly used for
geographical disease surveillance and cluster detection. These models, suitable for count …

Disease Mapping: From Foundations to Multidimensional Modeling guides the reader from
the basics of disease mapping to the most advanced topics in this field. A multidimensional …

Survival data often contain spatial information, such as the residence. In many cases the
impact of such spatial effects on hazard rates is of considerable interest. We propose flexible …

ABSTRACT A comprehensive, unified approach to modeling arbitrarily censored spatial
survival data is presented for the three most commonly used semiparametric models …

Several recent papers (eg,, Journal of the American Statistical Association 94, 909–919;,
Biometrics 57, 383–388) have described statistical methods for use with time-to-event data …