Log Gaussian Cox processes on the sphere

被引:5
|
作者
Cuevas-Pacheco, Francisco [1 ]
Moller, Jesper [1 ]
机构
[1] Aalborg Univ, Dept Math Sci, Aalborg, Denmark
关键词
Holder continuity; Pair correlation function; Point processes on the sphere; Reduced Palm distribution; Second order intensity reweighted homogeneity; Thinning procedure for model checking; POINT; STATISTICS;
D O I
10.1016/j.spasta.2018.06.002
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
A log Gaussian Cox process (LGCP) is a doubly stochastic construction consisting of a Poisson point process with a random log-intensity given by a Gaussian random field. Statistical methodology have mainly been developed for LGCPs defined in the d-dimensional Euclidean space. This paper concerns the case of LGCPs on the d-dimensional sphere, with d = 2 of primary interest. We discuss the existence problem of such LGCPs, provide sufficient existence conditions, and establish further useful theoretical properties. The results are applied for the description of sky positions of galaxies, in comparison with previous analysis based on a Thomas process, using simple estimation procedures and making a careful model checking. We account for inhomogeneity in our models, and as the model checking is based on a thinning procedure which produces homogeneous/isotropic LGCPs, we discuss its sensitivity. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:69 / 82
页数:14
相关论文
共 50 条
  • [1] Log Gaussian Cox processes
    Moller, J
    Syversveen, AR
    Waagepetersen, RP
    [J]. SCANDINAVIAN JOURNAL OF STATISTICS, 1998, 25 (03) : 451 - 482
  • [2] Palm Distributions for Log Gaussian Cox Processes
    Coeurjolly, Jean-Francois
    Moller, Jesper
    Waagepetersen, Rasmus
    [J]. SCANDINAVIAN JOURNAL OF STATISTICS, 2017, 44 (01) : 192 - 203
  • [3] Spatiotemporal prediction for log-Gaussian Cox processes
    Brix, A
    Diggle, PJ
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2001, 63 : 823 - 841
  • [4] Convergence of posteriors for discretized log Gaussian Cox processes
    Waagepetersen, R
    [J]. STATISTICS & PROBABILITY LETTERS, 2004, 66 (03) : 229 - 235
  • [5] Regularized estimation for highly multivariate log Gaussian Cox processes
    Choiruddin, Achmad
    Cuevas-Pacheco, Francisco
    Coeurjolly, Jean-Francois
    Waagepetersen, Rasmus
    [J]. STATISTICS AND COMPUTING, 2020, 30 (03) : 649 - 662
  • [6] Numerical Approximations of Log Gaussian Cox Processes (Student Abstract)
    Buet-Golfouse, Francois
    Roggeman, Hans
    [J]. THIRTY-SIXTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FOURTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE / TWELVETH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2022, : 12923 - 12924
  • [7] Regularized estimation for highly multivariate log Gaussian Cox processes
    Achmad Choiruddin
    Francisco Cuevas-Pacheco
    Jean-François Coeurjolly
    Rasmus Waagepetersen
    [J]. Statistics and Computing, 2020, 30 : 649 - 662
  • [8] On new families of anisotropic spatial log-Gaussian Cox processes
    Fariba Nasirzadeh
    Zohreh Shishebor
    Jorge Mateu
    [J]. Stochastic Environmental Research and Risk Assessment, 2021, 35 : 183 - 213
  • [9] On new families of anisotropic spatial log-Gaussian Cox processes
    Nasirzadeh, Fariba
    Shishebor, Zohreh
    Mateu, Jorge
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2021, 35 (02) : 183 - 213
  • [10] Bayesian Variable Selection Methods for Log-Gaussian Cox Processes
    Pinto Junior, Jony Arrais
    da Silva, Patricia Viana
    [J]. BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, MAXENT 37, 2018, 239 : 101 - 110