Testing the first-order separability hypothesis for spatio-temporal point patterns

Computational Statistics and Data Analysis - Tập 161 - Trang 107245 - 2021
Mohammad Ghorbani1, Nafiseh Vafaei2, Jiří Dvořák3, Mari Myllymäki4
1Department of Mathematics and Mathematical Statistics, Umeå University, Sweden
2Department of Computer and Statistics Sciences, Faculty of Sciences, Mohaghegh Ardabili University, Ardabil, Iran
3Department of Probability and Mathematical Statistics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic
4Natural Resources Institute Finland (Luke), Helsinki, Finland

Tài liệu tham khảo

Baddeley, 2000, Non- and semi-parametric estimation of interaction in inhomogeneous point patterns, Stat. Neerl., 54, 329, 10.1111/1467-9574.00144 Baddeley, 2016 Barnard, 1963, Discussion of professor Bartlett's paper, J. R. Stat. Soc., Ser. B, 25, 294 Beneš, 2015, Space-time models in stochastic geometry, 205 Besag, 1977, Simple Monte Carlo tests for spatial pattern, J. R. Stat. Soc., Ser. C, 26, 327 Bivand, 2013 Blum, 1961, Distribution free tests of independence based on the sample distribution function, Ann. Math. Stat., 32, 485, 10.1214/aoms/1177705055 Cronie, 2015, A J-function for inhomogeneous spatio-temporal point processes, Scand. J. Stat., 42, 562, 10.1111/sjos.12123 Daley, 2008 Diaz-Avalos, 2013, Similarity measures of conditional intensity functions to test separability in multidimensional point processes, Stoch. Environ. Res. Risk Assess., 27, 1193, 10.1007/s00477-012-0654-1 Diggle, 2007, Spatio-temporal point processes: methods and applications, 1 Diggle, 1985, A kernel method for smoothing point process data, Appl. Stat., 34, 138, 10.2307/2347366 Diggle, 2006, Spatio-temporal point processes, partial likelihood, foot and mouth disease, Stat. Methods Med. Res., 15, 325, 10.1191/0962280206sm454oa Diggle, 2013 Diggle, 2010, Spatio-temporal point processes, 451 Fuentes-Santos, 2018, A first-order, ratio-based nonparametric separability test for spatiotemporal point processes, Environmetrics, 29, 1, 10.1002/env.2482 Gabriel, 2009, Second-order analysis of inhomogeneous spatio-temporal point process data, Stat. Neerl., 63, 43, 10.1111/j.1467-9574.2008.00407.x Gabriel, E., Diggle, P.J., Rowlingson, B., Rodriguez-Cortes, F.J., 2018. Stpp: Space-time point pattern simulation, visualisation and analysis. R package version 2.0-3. Ghorbani, 2013, Testing the weak stationarity of a spatio-temporal point process, Stoch. Environ. Res. Risk Assess., 27, 517, 10.1007/s00477-012-0597-6 Gonzalez, 2020, Analysis of tornado reports through replicated spatio temporal point patterns, J. R. Stat. Soc., Ser. C, 69, 3, 10.1111/rssc.12375 Illian, 2008 Keeling, 2001, Dynamics of the 2001 UK foot-and-mouth epidemic dispersal in a heterogeneous landscape, Science, 294, 813, 10.1126/science.1065973 Koňasová, 2021, Stochastic reconstruction for inhomogeneous point patterns, Methodol. Comput. Appl. Probab., 10.1007/s11009-019-09738-0 Loosmore, 2006, Statistical inference using the G or K point pattern spatial statistics, Ecol. Soc. Am., 87, 1925 Lotwick, 1982, Methods for analysing spatial point processes of several types of points, J. R. Stat. Soc., Ser. B, 44, 406 Møller, 2019, Structured space-sphere point processes and K-functions, Methodol. Comput. Appl. Probab., 10.1007/s11009-019-09712-w Møller, 2012, Aspects of second-order analysis of structured inhomogeneous spatio-temporal point processes, Stat. Neerl., 66, 472, 10.1111/j.1467-9574.2012.00526.x Møller, 2015, Functional summary statistics for the Johnson-Mehl model, J. Stat. Comput. Simul., 85, 899, 10.1080/00949655.2013.850691 Møller, 1998, Log Gaussian Cox processes, Scand. J. Stat., 25, 451, 10.1111/1467-9469.00115 Mrkvička, 2020, Revisiting the random shift approach for testing in spatial statistics, Spat. Stat. Mrkvička, 2020, A one-way ANOVA test for functional data with graphical interpretation, Kybernetika, 56, 432 Mrkvička Myllymäki Myllymäki, 2017, Global envelope tests for spatial processes, J. R. Stat. Soc., Ser. B, 79, 381, 10.1111/rssb.12172 Narisetty, 2016, Extremal depth for functional data and applications, J. Am. Stat. Assoc., 111, 1705, 10.1080/01621459.2015.1110033 2019 Schlather, 2015, Analysis, simulation and prediction of multivariate random fields with package Randomfields, J. Stat. Softw., 63, 1, 10.18637/jss.v063.i08 Schoenberg, 2004, Testing separability in spatial-temporal marked point processes, Biometrics, 60, 471, 10.1111/j.0006-341X.2004.00192.x Schoenberg, 2002, Point processes, spatial-temporal, 1573 Sheather, 1991, A reliable data-based bandwidth selection method for kernel density estimation, J. R. Stat. Soc., Ser. B, 53, 683 Tscheschel, 2006, Statistical reconstruction of random point patterns, Comput. Stat. Data Anal., 51, 859, 10.1016/j.csda.2005.09.007 Wiegand, 2013, A systematic comparison of summary characteristics for quantifying point patterns in ecology, Ecography, 36, 92, 10.1111/j.1600-0587.2012.07361.x Wood, 1994, Simulation of stationary Gaussian processes in [0,1]d, J. Comput. Graph. Stat., 3, 409