On the Voronoi estimator for the intensity of an inhomogeneous planar Poisson process
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[1] Robin Sibson,et al. Computing Dirichlet Tessellations in the Plane , 1978, Comput. J..
[2] R. E. Miles,et al. Monte carlo estimates of the distributions of the random polygons of the voronoi tessellation with respect to a poisson process , 1980 .
[3] P. Diggle. A Kernel Method for Smoothing Point Process Data , 1985 .
[4] C. D. Kemp,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[5] Mark Berman,et al. Approximating point process likelihoods with GLIM. , 1993 .
[6] Ebeling,et al. Detecting structure in two dimensions combining Voronoi tessellation and percolation. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.
[7] G. Godefroy,et al. Evaluation of neuronal numerical density by Dirichlet tessellation , 1994, Journal of Neuroscience Methods.
[8] Y. Kagan,et al. Long‐term probabilistic forecasting of earthquakes , 1994 .
[9] N. Cressie,et al. Asymptotic Properties of Estimators for the Parameters of Spatial Inhomogeneous Poisson Point Processes , 1994, Advances in Applied Probability.
[10] Enzo Boschi,et al. Forecasting where larger crustal earthquakes are likely to occur in Italy in the near future , 1995, Bulletin of the Seismological Society of America.
[11] J. Egozcue,et al. Bayesian estimation of seismic hazard for two sites in Switzerland , 1996 .
[12] D. Brillinger,et al. Some wavelet analyses of point process data , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).
[13] Daryl J. Daley,et al. An Introduction to the Theory of Point Processes , 2013 .
[14] J. Heikkinen,et al. Non‐parametric Bayesian Estimation of a Spatial Poisson Intensity , 1998 .
[15] Adrian Baddeley,et al. Practical maximum pseudolikelihood for spatial point patterns , 1998, Advances in Applied Probability.
[16] Y. Ogata. Space-Time Point-Process Models for Earthquake Occurrences , 1998 .
[17] Qiang Du,et al. Centroidal Voronoi Tessellations: Applications and Algorithms , 1999, SIAM Rev..
[18] A. Baddeley,et al. Practical Maximum Pseudolikelihood for Spatial Point Patterns , 1998, Advances in Applied Probability.
[19] G. Godefroy,et al. Voronoi tessellation to study the numerical density and the spatial distribution of neurones , 2000, Journal of Chemical Neuroanatomy.
[20] Y. Kagan,et al. Probabilistic forecasting of earthquakes , 2000 .
[21] F. Evison. Long-range synoptic earthquake forecasting: an aim for the millennium , 2001 .
[22] Andrew Hayen,et al. Areas of components of a Voronoi polygon in a homogeneous Poisson process in the plane , 2002, Advances in Applied Probability.
[23] Cheng Li,et al. Inverting Dirichlet Tessellations , 2003, Comput. J..
[24] M. Tanemura. Statistical Distributions of Poisson Voronoi Cells in Two and Three Dimensions , 2003 .
[25] Frederic Paik Schoenberg,et al. Multidimensional Residual Analysis of Point Process Models for Earthquake Occurrences , 2003 .
[26] G. Nason,et al. A Haar-Fisz Algorithm for Poisson Intensity Estimation , 2004 .
[27] B. Coull,et al. Modelling spatial intensity for replicated inhomogeneous point patterns in brain imaging , 2004 .
[28] F. Schoenberg. Consistent Parametric Estimation of the Intensity of a Spatial-temporal Point Process , 2005 .
[29] Harald Haas,et al. Asilomar Conference on Signals, Systems, and Computers , 2006 .
[30] Yongtao Guan,et al. A Composite Likelihood Approach in Fitting Spatial Point Process Models , 2006 .
[31] Yongtao Guan,et al. On least squares fitting for stationary spatial point processes , 2007 .
[32] Yongtao Guan. On Consistent Nonparametric Intensity Estimation for Inhomogeneous Spatial Point Processes , 2008 .