271 citations · 319 across the 17 of their papers we have counts for
8 papers · 1 filter
Interoperability of statistical models in pandemic preparedness: principles and reality
George Nicholson, Marta Blangiardo, Mark Briers +12
We present "interoperability" as a guiding framework for statistical modelling to assist policy makers asking multiple questions using diverse datasets in the face of an evolving p…
The -family of covariance functions: A Matérn analogue for modeling random fields on spheres
Alfredo Alegría, Francisco Cuevas-Pacheco, Peter Diggle +1
The Mat{é}rn family of isotropic covariance functions has been central to the theoretical development and application of statistical models for geospatial data. For global data def…
A Spatially Discrete Approximation to Log-Gaussian Cox Processes for Modelling Aggregated Disease Count Data
Olatunji Johnson, Peter Diggle, Emanuele Giorgi
In this paper, we develop a computationally efficient discrete approximation to log-Gaussian Cox process (LGCP) models for the analysis of spatially aggregated disease count data.…
Linear Mixed-Effects Models for Non-Gaussian Repeated Measurement Data
Özgür Asar, David Bolin, Peter J. Diggle +1
We consider the analysis of continuous repeated measurement outcomes that are collected through time, also known as longitudinal data. A standard framework for analysing data of th…
Geostatistical methods for disease mapping and visualization using data from spatio-temporally referenced prevalence surveys
Emanuele Giorgi, Peter J. Diggle, Robert W. Snow +1
In this paper we set out general principles and develop geostatistical methods for the analysis of data from spatio-temporally referenced prevalence surveys. Our objective is to pr…
Inhibitory geostatistical designs for spatial prediction taking account of uncertain covariance structure
Michael G. Chipeta, Dianne J. Terlouw, Kamija S. Phiri +1
The problem of choosing spatial sampling designs for investigating unobserved spatial phenomenon S arises in many contexts, for example in identifying households to select for a pr…
Adaptive Geostatistical Design and Analysis for Sequential Prevalence Surveys
Michael G. Chipeta, Dianne J. Terlouw, Kamija Phiri +1
Non-adaptive geostatistical designs (NAGD) offer standard ways of collecting and analysing geostatistical data in which sampling locations are fixed in advance of any data collecti…
Spatial and Spatio-Temporal Log-Gaussian Cox Processes: Extending the Geostatistical Paradigm
Peter J. Diggle, Paula Moraga, Barry Rowlingson +1
In this paper we first describe the class of log-Gaussian Cox processes (LGCPs) as models for spatial and spatio-temporal point process data. We discuss inference, with a particula…