Due to the increasing availability of spatial or spatio-temporal regression data, models that
allow to incorporate the special structure of such data sets in an appropriate way are highly …

In many applications of survival data analysis, the individuals are treated in different medical
centres or belong to different clusters defined by geographical or administrative regions. The …

In common with most scientific texts this one is the result of several iterations. The seed for
the iterations was the 2008 text Proportional Hazards Regression and the first step was in …

Background Previous studies suggest spatial differences in mortality for many types of
cancer, including breast cancer. Identifying explanations for these spatial differences results …

This paper introduces spatial moving average risk smoothing (SMARS) as a new way of
carrying out disease mapping. This proposal applies the moving average ideas of time …

This paper addresses the problem of specifying, estimating, and validating Weibull hazard
rate models for water distribution networks under incomplete data. The most notable …

Rapid developments in geographical information systems (GIS) continue to generate
interest in analyzing complex spatial datasets. One area of activity is in creating smoothed …

Incorporating spatial variation could potentially enhance information coming from survival
data. In addition, simultaneous (joint) modeling of time‐to‐event data from different …

Mixtures of Polya trees offer a very flexible nonparametric approach for modelling time-to-
event data. Many such settings also feature spatial association that requires further …

Survival methods are used for the statistical modelling of time-to-event data. Survival data
are characterized by a set of complete records, in which the time of the event is known; and …