| Spatial point patterns: methodology and applications with R A Baddeley, E Rubak, R Turner CRC press, 2015 | 2586 | 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 | 282 | 2015 |
| Logistic regression for spatial Gibbs point processes A Baddeley, JF Coeurjolly, E Rubak, R Waagepetersen Biometrika 101 (2), 377-392, 2014 | 85 | 2014 |
| 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 | 49 | 2019 |
| Determinantal point process models on the sphere J Møller, M Nielsen, E Porcu, E Rubak | 42 | 2018 |
| Score, pseudo-score and residual diagnostics for spatial point process models A Baddeley, E Rubak, J Møller | 39 | 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 | 35 | 2013 |
| 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 | 28 | 2016 |
| Statistical aspects of determinantal point processes F Lavancier, J Møller, E Rubak | 26 | 2012 |
| Spatial point pattern analysis, model-fitting, simulation, tests A Baddeley, R Turner Recuperado el 15, 2017 | 24 | 2017 |
| Package spatstat: spatial point pattern analysis, model-fitting, simulation, tests A Baddeley, R Turner, E Rubak Online: http://cran. r-project. org, 2014 | 16 | 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 | 15 | 2016 |
| 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 | 12 | 2016 |
| A model for positively correlated count variables J Møller, E Rubak International statistical review 78 (1), 65-80, 2010 | 11 | 2010 |
| Using the R package spatstat to assess inhibitory effects of microregional hypoxia on the infiltration of cancers of the head and neck region by cytotoxic T lymphocytes J Kaufmann, CAN Biscio, P Bankhead, S Zimmer, H Schmidberger, ... Cancers 13 (8), 1924, 2021 | 8 | 2021 |
| Getting started with spatstat A Baddeley, R Turner, E Rubak For spatstat version, 1.36-0, 2014 | 8 | 2014 |
| Leverage and influence diagnostics for Gibbs spatial point processes A Baddeley, E Rubak, R Turner Spatial statistics 29, 15-48, 2019 | 7 | 2019 |
| Statistical inference for a class of multivariate negative binomial distributions EH Rubak, J Møller, P McCullagh Department of Mathematical Sciences, Aalborg University, 2010 | 6 | 2010 |
| The spatstat package A Baddeley, R Turner, E Rubak Spatial point pattern analysis, model-fitting, simulation, tests, 2006 | 5 | 2006 |
| Score, pseudo-score and residual diagnostics for goodness-of-fit of spatial point process models A Baddeley, EH Rubak, J Møller | 3 | 2010 |