Area-interaction point processes
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Baddeley, A. J. and Gill, R. D. (1992). Kaplan-Meier estimators for interpoint distance distributions of spatial point processes, Research Report, 718, Mathematical Institute, University of Utrecht. The Netherlands.
Baddeley, A. J. and Møller, J. (1989). Nearest-neighbour Markov point processes and random sets,Internat. Statist. Rev.,57, 89–121.
Baddeley, A. J. and Van Lieshout, M. N. M. (1991). Recognition of overlapping objects using Markov spatial models, Tech. Report, BS-R9109, CWI, Amsterdam.
Baddeley, A. J. and Van Lieshout, M. N. M. (1992). ICM for object recognition,Computational Statistics (eds. Y. Dodge and J. Whittaker), Vol. 2, 271–286, Physica/Springer, Heidelberg.
Baddeley, A. J. and Van Lieshout, M. N. M. (1993). Stochastic geometry models in high-level vision,Statistics and Images (eds. K. Mardia and G. K. Kanji), Vol. 1,Journal of Applied Statistics,20, 233–258, Carfax, Abingdon.
Besag, J. (1974). Spatial interaction and the statistical analysis of lattice systems (with discussion).J. Roy. Statist. Soc. Ser. B,36, 192–236.
Besag, J. (1977). Some methods of statistical analysis for spatial data,Bull. Internat. Statist. Inst.,47, 77–92.
Besag, J., Milne, R. and Zachary, S. (1982). Point process limits of lattice processes,J. Appl. Probab.,19, 210–216.
Cressie, N. A. C. (1991).Statistics for Spatial Data, Wiley, New York.
Daley, D. J. and Vere-Jones, D. (1988).An Introduction to the Theory of Point Processes, Springer, New York.
Diggle, P. J. (1983).Statistical Analysis of Spatial Point Patterns, Academic Press, London.
Diggle, P. J. and Gratton, R. J. (1984). Monte Carlo methods of inference for implicit statistical models.J. Roy. Statist. Soc. Ser. B,46, 193–227.
Diggle, P. J., Gates, D. J. and Stibbard, A. (1987). A nonparametric estimator for pairwiseinteraction point processes,Biometrika,74, 763–770.
Diggle, P. J., Fiksel, T., Grabarnik, P., Ogata, Y., Stoyan, D. and Tanemura, M. (1994). On parameter estimation for pairwise interaction processes,Internat. Statist. Rev.,62, 99–117.
Fiksel, T. (1984). Estimation of parametrized pair potentials of marked and nonmarked Gibbsian point processes,Elektronische Informationsverarbeitung und Kybernetika,20, 270–278.
Fiksel, T. (1988). Estimation of interaction potentials of Gibbsian point processes,Statistics,19, 77–86.
Gates, D. J. and Westcott, M. (1986). Clustering estimates for spatial point distributions with unstable potentials,Ann. Inst. Statist. Math.,38, 123–135.
Geyer, C. J. and Møller, J. (1993). Simulation procedures and likelihood inference for spatial point processes. Research Report, 260, Mathematical Institute, University of Aarhus, Denmark.
Geyer, C. J. and Thompson, E. A. (1992). Constrained Monte Carlo maximum likelihood for dependent data (with discussion),J. Roy. Statist. Soc. Ser. B,54, 657–699.
Hall, P. (1988).An Introduction to the Theory of Coverage Processes, Wiley, New York.
Hammersley, J. M., Lewis, J. W. E. and Rowlinson, J. S. (1975). Relationships between the multinomial and Poisson models of stochastic processes, and between the canonical and grand canonical ensembles in statistical mechanics, with illustrations and Monte Carlo methods for the penetrable sphere model of liquid-vapour equilibrium,Sankhyā Ser. A,37, 457–491.
Illingworth, J. and Kittler, J. (1988). A survey of the Hough transform,Computer Vision, Graphics and Image Processing,44, 87–116.
Jensen, J. L. (1993). Asymptotic normality of estimates in spatial point processes,Scand. J. Statist.,20, 97–109.
Jensen, J. L. and Møller, J. (1991). Pseudolikelihood for exponential family models of spatial point processes,Annals of Applied Probability,1, 445–461.
Kallenberg, O. (1984). An informal guide to the theory of conditioning in point processes,Internat. Statist. Rev.,52, 151–164.
Kendall, W. S. (1990). A spatial Markov property for nearest-neighbour Markov point processes,J. Appl. Probab.,28, 767–778.
Lawson, A. (1993). Gibbs sampling putative pollution sources, Tech. Report, Dundee Institute of Technology (in preparation).
Van Lieshout, M. N. M. and Baddeley, A. J. (1995). A nonparametric measure of spatial interaction in point patterns,Statist. Neerlandica (in press).
Mase, S. (1990). Mean characteristics of Gibbsian point processes,Ann. Inst. Statist. Math.,42, 203–220.
Matheron, G. (1975).Random Sets and Integral Geometry, Wiley, New York.
Matthes, K., Warmuth, J. and Mecke, J. (1979). Bemerkungen zu einer Arbeit von X. X. Nguyen und H. Zessin,Math. Nachr.,88, 117–127.
Møller, J. (1989). On the rate of convergence of spatial birth-and-death processes,Ann. Inst. Statist. Math.,41, 565–581.
Møller, J. (1992). Discussion contribution,J. Roy. Statist. Soc. Ser. B,54, 692–693.
Møller, J. (1994). Markov chain Monte Carlo and spatial point processes, Research Report, 293, Mathematical Institute, University of Aarhus, Denmark.
Moyeed, R. A. and Baddeley, A. J. (1991). Stochastic approximation for the MLE of a spatial point process,Scand. J. Statist.,18, 39–50.
Nguyen, X. X. and Zessin, H. (1979). Integral and differential characterization of the Gibbs process,Math. Nachr.,88, 105–115.
Ogata, Y. and Tanemura, M. (1981). Estimation for interaction potentials of spatial point patterns through the maximum likelihood procedure,Ann. Inst. Statist. Math.,33, 315–338.
Ogata, Y. and Tanemura, M. (1984). Likelihood analysis of spatial point patterns,J. Roy. Statist. Soc. Ser. B,46, 496–518.
Ogata, Y. and Tanemura, M. (1989). Likelihood estimation of soft-core interaction potentials for Gibbsian point patterns,Ann. Inst. Statist. Math.,41, 583–600.
Penttinen, A. (1984).Modelling Interaction in Spatial Point Patterns: Parameter Estimation by the Maximum Likelihood Method, Number 7 in Jyväskylä Studies in Computer Science, Economics and Statistics, University of Jyvaskyla.
Preston, C. J. (1977). Spatial birth-and-death processes,Bull. Internat. Statist. Inst.,46, 371–391.
Ripley, B. D. (1977). Modelling spatial patterns (with discussion),J. Roy. Statist. Soc. Ser. B,39, 172–212.
Ripley, B. D. (1989). Gibbsian interaction models,Spatial Statistics: Past, Present and Future (ed. D. A. Griffiths), 1–19, Image, New York.
Rosenfeld, A. and Pfalz, J. L. (1968). Distance functions on digital pictures, Pattern Recognition,1, 33–61.
Rowlinson, J. S. (1980). Penetrable sphere models of liquid-vapor equilibrium,Adv. Chem. Phys.,41, 1–57.
Rowlinson, J. S. (1990). Probability densities for some one-dimensional problems in statistical mechanics,Disorder in Physical Systems (eds. G. R. Grimmett and D. J. A. Welsh), 261–276, Clarendon Press, Oxford.
Ruelle, D. (1969).Statistical Mechanics, Wiley, New York.
Särkkä, A. (1989). On parameter estimation of Gibbs point processes through the pseudolikelihood estimation method, Research Report, 4, Department of Statistics, University of Jyväskylä, Finland.
Särkkä, A. (1990). Applications of Gibbs point processes: pseudo-likelihood method with comparisons, Research Report, 10, Department of Statistics, University of Jyväskylä, Finland.
Stoyan, D. and Stoyan, H. (1992).Fraktale—Formen—Punktfelder, Akademie Verlag, Berlin.
Stoyan, D., Kendall, W. S. and Mecke, J. (1987).Stochastic Geometry and Its Applications, Wiley, Chichester.
Takacs, R. (1983). Estimator for the pair-potential of a Gibbsian point process, Institutsbericht, 238, Institut für Mathematik, Johannes Kepler Universität Linz, Austria.
Takacs, R. (1986). Estimator for the pair potential of a Gibbsian point process,Statistics,17, 429–433.