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DETECTING LINEAR FEATURES BY SPATIAL POINT PROCESSES
Linear Feature Feature Detection Spatial Point Processes Global Optimization Simulated Annealing Markov Chain Monte Carlo
2016/7/28
This paper proposes a novel approach for linear feature detection. The contribution is twofold: a novel model for spatial point processes and a new method for linear feature detection. It describes a ...
Quasi-likelihood for Spatial Point Processes
Estimating function Fredholm integral equation Godambe information Int function Quasi-likelihood Regression model Spatial point process.
2013/4/27
Fitting regression models for intensity functions of spatial point processes is of great interest in ecological and epidemiological studies of association between spatially referenced events and geogr...
Quasi-likelihood for Spatial Point Processes
Estimating function Fredholm integral equation Godambe information Int function Quasi-likelihood Regression model Spatial point process.
2013/4/27
Fitting regression models for intensity functions of spatial point processes is of great interest in ecological and epidemiological studies of association between spatially referenced events and geogr...
Modelling fixation locations using spatial point processes
Modelling fixation locations spatial point processes
2012/9/19
Whenever eye movements are measured, a central part of the analysis has to do withwheresubjects fixate, andwhy they fixated where they fixated. To a first approximation, a set of fixations can be view...
Perfect simulation of spatial point processes using dominated coupling from the past with application to a multiscale area-interaction point process
Perfect simulation spatial point processes dominated coupling multiscale area-interaction point process
2010/3/18
We consider perfect simulation algorithms for locally stable point pro-
cesses based on dominated coupling from the past. A version of the al-
gorithm is developed which is feasible for processes wh...
On the Threshold Method for Marked Spatial Point Processes
linear prediction mixing condition non-ergodicity
2009/3/10
The threshold method in the framework of marked spatial point processes on a continuous space is discussed. The threshold method is a linear prediction of the total sum of marks using only the number ...
Bayesian Estimation of Soft-Core Potential Models for Spatial Point Patterns
Bayesian estimation L-statistics MCMC methods repulsive interaction Soft-Core models
2009/3/6
For a spatial pattern of points interacting with a repulsive potential in a given finite region of the plane, Bayesian estimation of parametric interaction potential functions between individuals (the...
Prediction of the Sample Variance of Marks for a Marked Spatial Point Process by the Threshold Method
marked spatial point process mean square error mixing condition non-ergodicity threshold method
2009/3/6
We discuss the prediction of the sample variance of marks of a marked spatial point process on a continuous space by the threshold method. The threshold method is a statistical prediction using only t...