Spatial cluster modelling of small area disease incidence and mortality has previously focused on clusters where excess risk is distributed around fixed points, and the aim is the reconstruction of these points (cluster centers). Often there is a need to assess clusters of a different form, such as around roads or river systems. These clusters are often linear or can be approximated by combinations of several linear segments. In this paper the recovery of point and line clusters is considered jointly. An example application is given where both linear or point clustering could be present.
Line and point cluster models for spatial health data / A.B. LAWSON; S. SIMEON; M. KULLDORFF; A. BIGGERI. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - STAMPA. - 51:(2007), pp. 6027-6043.
Line and point cluster models for spatial health data
BIGGERI, ANNIBALE
2007
Abstract
Spatial cluster modelling of small area disease incidence and mortality has previously focused on clusters where excess risk is distributed around fixed points, and the aim is the reconstruction of these points (cluster centers). Often there is a need to assess clusters of a different form, such as around roads or river systems. These clusters are often linear or can be approximated by combinations of several linear segments. In this paper the recovery of point and line clusters is considered jointly. An example application is given where both linear or point clustering could be present.File | Dimensione | Formato | |
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