Ege Rubak
Title
Cited by
Cited by
Year
Spatial point patterns: methodology and applications with R
A Baddeley, E Rubak, R Turner
CRC press, 2015
9502015
Determinantal point process models and statistical inference
F Lavancier, J Møller, E Rubak
Journal of the Royal Statistical Society: Series B: Statistical Methodology …, 2015
1692015
Package ‘spatstat’
A Baddeley, R Turner
The Comprehensive R Archive Network (), 2014
63*2014
Logistic regression for spatial Gibbs point processes
A Baddeley, JF Coeurjolly, E Rubak, R Waagepetersen
Biometrika 101 (2), 377-392, 2014
462014
Logistic regression for spatial Gibbs point processes
A Baddeley, JF Coeurjolly, E Rubak, R Waagepetersen
Biometrika 101 (2), 377-392, 2014
462014
Score, pseudo-score and residual diagnostics for spatial point process models
A Baddeley, E Rubak, J Møller
Statistical Science 26 (4), 613-646, 2011
302011
Score, pseudo-score and residual diagnostics for spatial point process models
A Baddeley, E Rubak, J Møller
Statistical Science 26 (4), 613-646, 2011
302011
Determinantal point process models on the sphere
J Møller, M Nielsen, E Porcu, E Rubak
Bernoulli 24 (2), 1171-1201, 2018
292018
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
232013
Statistical aspects of determinantal point processes
F Lavancier, J Møller, E Rubak
Department of Mathematical Sciences, Aalborg University, 2012
212012
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
122016
Package Spatstat: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
A Baddeley, R Turner, E Rubak
Online: http://cran. r-project. org, 2014
112014
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
102016
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
92019
A model for positively correlated count variables
J Møller, E Rubak
International statistical review 78 (1), 65-80, 2010
62010
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
42016
Statistical inference for a class of multivariate negative binomial distributions
E Rubak, J Møller, P McCullagh
Department of Mathematical Sciences, Aalborg University, 2010
42010
The spatstat package
A Baddeley, R Turner, MA Baddeley
Spatial point pattern analysis, model-fitting, simulation, tests, 2006
42006
Getting started with spatstat
A Baddeley, R Turner, E Rubak
For spatstat version, 1.36-0, 2014
32014
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
32010
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Articles 1–20