Spatial point patterns: methodology and applications with R A Baddeley, E Rubak, R Turner Chapman and Hall/CRC, 2015 | 807 | 2015 |

Determinantal point process models and statistical inference F Lavancier, J Møller, E Rubak Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2015 | 148 | 2015 |

Logistic regression for spatial Gibbs point processes A Baddeley, JF Coeurjolly, E Rubak, R Waagepetersen Biometrika 101 (2), 377-392, 2014 | 44 | 2014 |

Logistic regression for spatial Gibbs point processes A Baddeley, JF Coeurjolly, E Rubak, R Waagepetersen Biometrika 101 (2), 377-392, 2014 | 44 | 2014 |

Determinantal point process models on the sphere J Møller, M Nielsen, E Porcu, E Rubak Bernoulli 24 (2), 1171-1201, 2018 | 27 | 2018 |

Spatstat: spatial point pattern analysis, model-fitting, simulation, tests A Baddeley, R Turner, E Rubak R Foundation for Statistical Computing, Vienna, Austria, 2013 | 26 | 2013 |

Package ‘spatstat’ A Baddeley, R Turner The Comprehensive R Archive Network (), 2014 | 25* | 2014 |

Score, pseudo-score and residual diagnostics for spatial point process models A Baddeley, E Rubak, J Møller Statistical Science 26 (4), 613-646, 2011 | 22 | 2011 |

Score, pseudo-score and residual diagnostics for spatial point process models A Baddeley, E Rubak, J Møller Statistical Science 26 (4), 613-646, 2011 | 22 | 2011 |

Fast covariance estimation for innovations computed from a spatial Gibbs point process JF Coeurjolly, E Rubak Scandinavian Journal of Statistics 40 (4), 669-684, 2013 | 21 | 2013 |

Statistical aspects of determinantal point processes F Lavancier, J Møller, E Rubak Department of Mathematical Sciences, Aalborg University, 2012 | 18 | 2012 |

Functional summary statistics for point processes on the sphere with an application to determinantal point processes J Møller, E Rubak Spatial Statistics 18, 4-23, 2016 | 10 | 2016 |

Package Spatstat: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests A Baddeley, R Turner, E Rubak Online: http://cran. r-project. org, 2014 | 10 | 2014 |

Mechanistic spatio‐temporal point process models for marked point processes, with a view to forest stand data J Møller, M Ghorbani, E Rubak Biometrics 72 (3), 687-696, 2016 | 9 | 2016 |

A model for positively correlated count variables J Møller, E Rubak International statistical review 78 (1), 65-80, 2010 | 6 | 2010 |

Resample-smoothing of Voronoi intensity estimators MM Moradi, O Cronie, E Rubak, R Lachieze-Rey, J Mateu, A Baddeley Statistics and computing 29 (5), 995-1010, 2019 | 5 | 2019 |

Adjusted composite likelihood ratio test for spatial Gibbs point processes A Baddeley, R Turner, E Rubak Journal of Statistical Computation and Simulation 86 (5), 922-941, 2016 | 4 | 2016 |

Statistical inference for a class of multivariate negative binomial distributions E Rubak, J Møller, P McCullagh Department of Mathematical Sciences, Aalborg University, 2010 | 4 | 2010 |

The spatstat package A Baddeley, R Turner, MA Baddeley Spatial point pattern analysis, model-fitting, simulation, tests, 2006 | 4 | 2006 |

Score, pseudo-score and residual diagnostics for goodness-of-fit of spatial point process models A Baddeley, E Rubak, J Møller Department of Mathematical Sciences, Aalborg University, 2010 | 3 | 2010 |