155 citations · 189 across the 9 of their papers we have counts for
10 papers
Data Fusion in a Two-stage Spatio-Temporal Model using the INLA-SPDE Approach
Stephen Jun Villejo, Janine B Illian, Ben Swallow
This paper proposes a two-stage estimation approach for a spatial misalignment scenario that is motivated by the epidemiological problem of linking pollutant exposures and health o…
Careful prior specification avoids incautious inference for log-Gaussian Cox point processes
Sigrunn H. Sørbye, Janine B. Illian, Daniel P. Simpson +1
Prior specifications for hyperparameters of random fields in Bayesian spatial point process modelling can have a major impact on the statistical inference and the conclusions made.…
Level set Cox processes
Anders Hildeman, David Bolin, Jonas Wallin +1
The log-Gaussian Cox process (LGCP) is a popular point process for modeling non-interacting spatial point patterns. This paper extends the LGCP model to handle data exhibiting fund…
Unusual structures inherent in point pattern data predict colon cancer patient survival
Charlotte M. Jones-Todd, Peter Caie, Janine Illian +4
Cancer patient diagnosis and prognosis is informed by assessment of morphological properties observed in patient tissue. Pathologists normally carry out this assessment, yet advanc…
A Bayesian Approach to Modelling Fine-Scale Spatial Dynamics of Non-State Terrorism: World Study, 2002-2013
André Python, Janine Illian, Charlotte Jones-Todd +1
To this day, terrorism persists as a worldwide threat, as exemplified by the ongoing lethal attacks perpetrated by ISIS in Iraq, Syria, Al Qaeda in Yemen, and Boko Haram in Nigeria…
Non-stationary Gaussian models with physical barriers
Haakon Bakka, Jarno Vanhatalo, Janine Illian +2
The classical tools in spatial statistics are stationary models, like the Matérn field. However, in some applications there are boundaries, holes, or physical barriers in the study…