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Adrian Baddeley
Curtin University
149Publications
35H-index
7,135Citations
Publications 149
Newest
#1M. Mehdi MoradiH-Index: 2
#2Ottmar Cronie (Umeå University)H-Index: 6
Last.Adrian Baddeley (Curtin University)H-Index: 35
view all 6 authors...
Voronoi estimators are non-parametric and adaptive estimators of the intensity of a point process. The intensity estimate at a given location is equal to the reciprocal of the size of the Voronoi/Dirichlet cell containing that location. Their major drawback is that they tend to paradoxically under-smooth the data in regions where the point density of the observed point pattern is high, and over-smooth where the point density is low. To remedy this behaviour, we propose to apply an additional smo...
1 CitationsSource
#1Greg McSwiggan (UWA: University of Western Australia)H-Index: 1
#2Adrian Baddeley (Curtin University)H-Index: 35
Last.Gopalan Nair (UWA: University of Western Australia)H-Index: 7
view all 3 authors...
Motivated by the study of traffic accidents on a road network, we discuss the estimation of the relative risk, the ratio of rates of occurrence of different types of events occurring on a network of lines. Methods developed for two-dimensional spatial point patterns can be adapted to a linear network, but their requirements and performance are very different on a network. Computation is slow and we introduce new techniques to accelerate it. Intensities (occurrence rates) are estimated by kernel ...
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#1Suman Rakshit (Curtin University)H-Index: 3
#2Tilman M. Davies (University of Otago)H-Index: 9
Last.Adrian Baddeley (Curtin University)H-Index: 35
view all 7 authors...
3 CitationsSource
#1Kassel Hingee (UWA: University of Western Australia)H-Index: 1
#2Adrian Baddeley (Curtin University)H-Index: 35
Last.Gopalan Nair (UWA: University of Western Australia)H-Index: 7
view all 4 authors...
We consider a spatial binary coverage map (binary pixel image) which might represent the spatial pattern of the presence and absence of vegetation in a landscape. ‘Lacunarity’ is a generic term for the nature of gaps in the pattern: a popular choice of summary statistic is the ‘gliding-box lacunarity’ (GBL) curve. GBL is potentially useful for quantifying changes in vegetation patterns, but its application is hampered by a lack of interpretability and practical difficulties with missing data. In...
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#1Adrian Baddeley (Curtin University)H-Index: 35
#2Ege Holger Rubak (AAU: Aalborg University)H-Index: 7
Last.Rolf Turner (University of Auckland)H-Index: 13
view all 3 authors...
Abstract For point process models fitted to spatial point pattern data, we describe diagnostic quantities analogous to the classical regression diagnostics of leverage and influence. We develop a simple and accessible approach to these diagnostics, and use it to extend previous results for Poisson point process models to the vastly larger class of Gibbs point processes. Explicit expressions, and efficient calculation formulae, are obtained for models fitted by maximum pseudolikelihood, maximum l...
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#1Suman Rakshit (Curtin University)H-Index: 3
#2Adrian Baddeley (Curtin University)H-Index: 35
Last.Gopalan NairH-Index: 7
view all 3 authors...
We describe efficient algorithms and open-source code for the second-order statistical analysis of point events on a linear network. Typical summary statistics are adaptations of Ripley's K-function and the pair correlation function to the case of a linear network, with distance measured by the shortest path in the network. Simple implementations consume substantial time and memory. For an efficient implementation, the data structure representing the network must be economical in its use of memo...
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#1Tilman M. Davies (University of Otago)H-Index: 9
#2Adrian Baddeley (Curtin University)H-Index: 35
Kernel smoothing of spatial point data can often be improved using an adaptive, spatially varying bandwidth instead of a fixed bandwidth. However, computation with a varying bandwidth is much more demanding, especially when edge correction and bandwidth selection are involved. This paper proposes several new computational methods for adaptive kernel estimation from spatial point pattern data. A key idea is that a variable-bandwidth kernel estimator for d-dimensional spatial data can be represent...
6 CitationsSource
#1Adrian Baddeley (Curtin University)H-Index: 35
We compare and contrast several statistical methods for predicting the occurrence of mineral deposits on a regional scale. Methods include logistic regression, Poisson point process modelling, maximum entropy, monotone regression, nonparametric curve estimation, recursive partitioning, and ROC (Receiver Operating Characteristic) curves. We discuss the use and interpretation of these methods, the relationships between them, their strengths and weaknesses from a statistical standpoint, and fallaci...
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1 CitationsSource
#1Suman Rakshit (Curtin University)H-Index: 3
#2Gopalan Nair (UWA: University of Western Australia)H-Index: 7
Last.Adrian Baddeley (Curtin University)H-Index: 35
view all 3 authors...
Abstract The analysis of clustering and correlation between points on a linear network, such as traffic accident locations on a street network, depends crucially on how we measure the distance between points. Standard practice is to measure distance by the length of the shortest path. However, this may be inappropriate and even fallacious in some applications. Alternative distance metrics include Euclidean, least-cost, and resistance distances. This paper develops a general framework for the sec...
7 CitationsSource
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