Voronoi residual analysis of spatial point process models with applications to California earthquake forecasts
暂无分享,去创建一个
Frederic Paik Schoenberg | Andrew Bray | F. Schoenberg | C. Barr | Andrew Bray | Ka Wong | Ka Wong | Christopher D. Barr
[1] A. Helmstetter,et al. Adaptive Spatiotemporal Smoothing of Seismicity for Long‐Term Earthquake Forecasts in California , 2012 .
[2] L. Meijering,et al. INTERFACE AREA, EDGE LENGTH, AND NUMBER OF VERTICES IN CRYSTAL AGGREGATES WITH RANDOM NUCLEATION , 2014 .
[3] Y. Kagan,et al. High-resolution Time-independent Grid-based Forecast for M ≥ 5 Earthquakes in California , 2007 .
[4] Adrian Baddeley,et al. Score, pseudo-score and residual diagnostics for goodness-of-fit of spatial point process models , 2010 .
[5] D. Stoyan,et al. Discussion article on the paper Residual analysis for spatial point processes by A. Baddeley, R. Turner, J. Moller and M. Hazelton , 2005 .
[6] Y. Ogata. Significant improvements of the space-time ETAS model for forecasting of accurate baseline seismicity , 2011 .
[7] F. Schoenberg,et al. Residual analysis methods for space--time point processes with applications to earthquake forecast models in California , 2011, 1202.6487.
[8] F. Schoenberg,et al. Point process modeling of wildfire hazard in Los Angeles County, California , 2011, 1108.0754.
[9] David A. Rhoades,et al. Efficient testing of earthquake forecasting models , 2011 .
[10] A. Baddeley,et al. Residual analysis for spatial point processes (with discussion) , 2005 .
[11] Thordis L. Thorarinsdottir. Calibration diagnostics for point process models via the probability integral transform , 2013 .
[12] Yongtao Guan. A goodness-of-fit test for inhomogeneous spatial Poisson processes , 2008 .
[13] Frederic Paik Schoenberg,et al. Multidimensional Residual Analysis of Point Process Models for Earthquake Occurrences , 2003 .
[14] M. Moore,et al. Monte carlo estimates of the distributions of the poisson voronoi tessellation , 1999 .
[15] J. D. Zechar,et al. Regional Earthquake Likelihood Models I: First-Order Results , 2013 .
[16] Edward H. Field,et al. Overview of the Working Group for the Development of Regional Earthquake Likelihood Models (RELM) , 2005 .
[17] Frederic Paik Schoenberg,et al. Transforming Spatial Point Processes into Poisson Processes , 1999 .
[18] Andrew B. Lawson,et al. A Deviance Residual for Heterogeneous Spatial Poisson Processes , 1993 .
[19] F. Schoenberg,et al. Assessment of Point Process Models for Earthquake Forecasting , 2013, 1312.5934.
[20] 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 .
[21] T. Jordan. Earthquake Predictability, Brick by Brick , 2006 .
[22] Jon E. Keeley,et al. The 2007 Southern California Wildfires: Lessons in Complexity , 2009 .
[23] F. Massey. The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .
[24] M. Tanemura. Statistical Distributions of Poisson Voronoi Cells in Two and Three Dimensions , 2003 .
[25] B. Ripley. The Second-Order Analysis of Stationary Point Processes , 1976 .
[26] Daryl J. Daley,et al. An Introduction to the Theory of Point Processes , 2013 .
[27] J. D. Zechar,et al. Likelihood-Based Tests for Evaluating Space–Rate–Magnitude Earthquake Forecasts , 2009 .
[28] A. P. Dawid,et al. Present position and potential developments: some personal views , 1984 .
[29] Yan Y. Kagan,et al. Testable Earthquake Forecasts for 1999 , 1999 .
[30] J. Møller,et al. Aalborg Universitet Properties of residuals for spatial point processes , 2022 .
[31] Giada Adelfio,et al. Point process diagnostics based on weighted second-order statistics and their asymptotic properties , 2009 .
[32] Frederic Paik Schoenberg,et al. Facilitated Estimation of ETAS , 2013 .
[33] Frederic Paik Schoenberg,et al. Evaluation of space–time point process models using super‐thinning , 2011 .
[34] Qiang Du,et al. Centroidal Voronoi Tessellations: Applications and Algorithms , 1999, SIAM Rev..
[35] A. F. Smith. Present Position and Potential Developments: Some Personal Views Bayesian Statistics , 1984 .
[36] Jiancang Zhuang,et al. Basic Models of Seismicity: Temporal Models , 2012 .
[37] Y. Ogata. Space-Time Point-Process Models for Earthquake Occurrences , 1998 .
[38] Frederic Paik Schoenberg,et al. Assessing Spatial Point Process Models Using Weighted K-functions: Analysis of California Earthquakes , 2006 .
[39] Danijel Schorlemmer,et al. First Results of the Regional Earthquake Likelihood Models Experiment , 2010 .
[40] A. Baddeley,et al. Practical Maximum Pseudolikelihood for Spatial Point Patterns , 1998, Advances in Applied Probability.
[41] S. Wiemer,et al. Earthquake Likelihood Model Testing , 2007 .
[42] Adrian Baddeley,et al. Score, Pseudo-Score and Residual Diagnostics for Spatial Point Process Models , 2011, 1205.3918.
[43] B. Malamud,et al. Characterizing wildfire regimes in the United States. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[44] Claudia Czado,et al. Predictive Model Assessment for Count Data , 2009, Biometrics.
[45] A. Baddeley,et al. Residual analysis for spatial point processes (with discussion) , 2005 .
[46] Danijel Schorlemmer,et al. RELM Testing Center , 2007 .
[47] P. Meyer,et al. Demonstration simplifiee d'un theoreme de Knight , 1971 .
[48] F. Schoenberg,et al. On the Voronoi estimator for the intensity of an inhomogeneous planar Poisson process , 2010 .
[49] E. Johnson,et al. Forest fires : behavior and ecological effects , 2001 .
[50] Lucile M. Jones,et al. When and where the aftershock activity was depressed: Contrasting decay patterns of the proximate large earthquakes in southern California , 2003 .