Publications and reports of Rasmus Waagepetersen

Books:

Journal publications (sorted by topic and publication date):

Theory and applications of spatial point processes

  1. Choiruddin, A., Gonzalez, J. A., Mateu, J., Fadlurohman, A. and Waagepetersen, R. (2024) Variable selection for inhomogeneous spatio-temporal Poisson point processes, in preparation.
  2. Jalilian, A., Cuevas-Pacheco, F., Xu, G. and Waagepetersen, R. (2024) Composite likelihood inference for space-time point processes, arXiv:2402.12548, submitted.
  3. Jalilian, A., Poinas, A., Xu, G. and Waagepetersen, R. (2024) A central limit theorem for a sequence of conditionally centered random fields, Bernouilli, to appear. arXiv:2301.08942.
  4. Svane, A. M., Biscio, C. A. N. and Waagepetersen R. (2024) A functional central limit theorem for the $K$-function with an estimated intensity function, Electronic Journal of Statistics, 18, 3706-3728.
  5. Hirsch, C., Bharti, A., Pedersen, T. and Waagepetersen, R. (2022) Bayesian inference for stochastic multipath radio channel models, IEEE Transactions on Antennas and Propagation, 71, 3460-3472.
  6. Svane, A. M., Stephensen, H. J. T. and Waagepetersen, R. (2022) A $K$-function for inhomogeneous random measures with geometric features, Spatial Statistics, 51, 100656.
  7. Chu, T., Guan, Y., Waagepetersen, R. and Xu, G. (2022) Quasi-likelihood for multivariate spatial point processes with semiparametric intensity functions, Spatial Statistics, 50, 100605.
  8. Xu, G., Liang, C., Waagepetersen, R. and Guan, Y. (2022) Semi-parametric goodness-of-fit test for clustered point processes with a shape-constrained pair correlation function, Journal of the American Statistical Society, 118, 2072-2087.
  9. Hessellund, K. B., Xu, G., Guan, Y. and Waagepetersen, R. (2022) Second-order semi-parametric inference for multivariate log Gaussian Cox processes, Journal of the Royal Statistical Society Series C, 71, 244-268.
  10. Hessellund, K. B., Xu, G., Guan, Y. and Waagepetersen, R. (2022) Semi-parametric multinomial logistic regression for multivariate point pattern data, Journal of the American Statistical Society, 117, 1500-1515.
  11. Choiruddin, A., Coeurjolly, J.F. and Waagepetersen, R. (2021) Information criteria for inhomogeneous spatial point processes, Australian & New Zealand Journal of Statistics, 63, 119-143.
  12. Shaw, T., Møller, J. and Waagepetersen, R. (2021) Globally intensity-reweighted estimators for $K$- and pair correlation functions, Australian & New Zealand Journal of Statistics, 63, 93-118.
  13. Hirsch, C., Bharti, A., Pedersen, T. and Waagepetersen, R. (2021) Maximum likelihood calibration of stochastic multipath radio channel models, IEEE Transactions on Antennas and Propagation, 69, 4058-4069.
  14. Lavancier, F., Poinas, A. and Waagepetersen, R. (2021) Adaptive estimating function inference for non-stationary determinantal point processes, Scandinavian Journal of Statistics, 48, 87-107.
  15. Xu, G., Zhao, C., Jalilian, A., Waagepetersen, R., Zhang, J. and Guan, Y. (2020) Nonparametric Estimation of the Pair Correlation Function of Replicated Inhomogeneous Point Processes, Electronic Journal of Statistics, 14, 3730-3765. Supplementary material.
  16. Choiruddin, A., Cuevas-Pacheco, F., Coeurjolly, J.F. and Waagepetersen, R. (2019) Regularized estimation for highly multivariate log Gaussian Cox processes, Statistics and Computing, 30, 649-662.
  17. Coeurjolly, J.F., Cuevas-Pacheco, F. and Waagepetersen, R. (2019) Second-order variational equations for spatial point processes with a view to pair correlation function estimation, Spatial Statistics, 30, 103-115.
  18. Jalilian, A., Guan, Y. and Waagepetersen, R. (2019) Orthogonal series estimation of the pair correlation function of a spatial point process, Statistica Sinica, 29, 769-787. arXiv: 1796502, doi:10.5705/ss.202017.0112.
  19. Biscio, C. A. N. and Waagepetersen, R. (2019) A general central limit theorem and subsampling variance estimator for $\alpha$-mixing point processes, Scandinavian Journal of Statistics, 46, 1168-1190.
  20. Xu, G., Waagepetersen, R. and Guan, Y. (2019) Stochastic Quasi-likelihood for Case-Control Point Pattern Data, Journal of the American Statistical Association, 114, 631-644.
  21. Gratzer, G. and Waagepetersen, R. (2018) Seed dispersal, microsites or competition - what drives gap regeneration in an old-growth forest ? - An application of spatial point process modelling, Forests, 9, 230, 11 pages.
  22. Jalilian, A. and Waagepetersen, R. (2018) Fast band width selection for estimation of the pair correlation function, Journal of Statistical Computation and Simulation, 88, 2001-2011.
  23. Biscio, C. A. N., Poinas, A. and Waagepetersen R. (2018) A note on gaps in proofs of central limit theorems, Statistics and Probability Letters, 135, 7-10.
  24. Deng, C., Waagepetersen, R.P., Wang, M. and Guan, Y. (2018) A fast spectral quasi-likelihood approach for spatial point processes, Statistics and Probability Letters, 133, 59-64.
  25. Deng, C., Guan, Y., Waagepetersen, R. and Zhang, J. (2017) Second-order quasi-likelihood for spatial point processes, Biometrics, 73, 1311-1320.
  26. Hooghoudt, J., Barroso, M. and Waagepetersen, R. (2017) Towards Bayesian inference of the spatial distribution of proteins from three-cube Förster resonance energy transfer data, Annals of Applied Statistics, 11, 1711-1737.
  27. Coeurjolly J.-F., Møller, J. and Waagepetersen, R. (2017) A tutorial on Palm distributions for spatial point processes, International Statistical Review, 85, 404-420. arXiv: 1512.05871.
  28. Møller, J. and Waagepetersen, R. (2017) Some recent developments in statistics for spatial point processes, Annual Review of Statistics and its Applications, 4, 317-342. arXiv: 1609.00908.
  29. Coeurjolly J.-F., Møller, J. and Waagepetersen, R. (2017) Palm distributions for log Gaussian Cox processes, Scandinavian Journal of Statistics, 44, 192-203.
  30. Couerjolly, J.-F., Guan, Y., Khanmohammadi, M. and Waagepetersen, R. (2016) Towards optimal Takacs-Fiksel estimation, Spatial Statistics, 18, 396-411. arXiv: 1512.06693.
  31. Waagepetersen, R., Guan, Y., Jalilian, A. and Mateu, J. (2016) Analysis of multi-species point patterns using multivariate log Gaussian Cox processes, Journal of the Royal Statistical Society, Series C, 65, 77-96.
  32. Khanmohammadi, M., Waagepetersen, R. and Sporring, J. (2015) Analysis of shape and spatial interaction of synaptic vesicles using data from focused ion beam scanning electron microscopy (FIB-SEM), Frontiers in Neuroanatomy, 9, article 116, 11 pages.
  33. Chang, X., Waagepetersen, R., Yu, H., Ma, X., Holford, T., Wang, R. and Guan, Y. (2015) Disease risk estimation by combining case-control data with aggregated information on the population at risk, Biometrics, 71, 114-121.
  34. Jalilian, A., Guan, Y., Mateu, J. and Waagepetersen, R. (2015) Multivariate product-shot-noise Cox models, Biometrics, 71, 1022-1033.
  35. Guan, Y., Jalilian, A. and Waagepetersen, R. (2015) Quasi-likelihood for spatial point processes, Journal of the Royal Statistical Society, Series B, 77, 677-697. Supplementary material.
  36. Deng, C., Waagepetersen, R. and Guan, Y. (2014) A combined estimating function approach for fitting stationary point process models, Biometrika, 101, 393-408.
  37. Huang, H., Ma, X., Waagepetersen, R., Holford, T., Wang, R., Risch, H., Mueller, L. and Guan, Y. (2014) A new estimation approach for combining epidemiological data from multiple sources, Journal of the American Statistical Association, 109, 11-23.
  38. Baddeley, A.J., Coeurjolly, J.F., Rubak, E. and Waagepetersen R. (2014) A logistic regression estimating function for Gibbs point processes, Biometrika, 101, 377-392.
  39. Shen, G., He, F., Waagepetersen, R., Sun, I-F., Hao, Z., Chen, Z-S. and Yu, M. (2013) Quantifying effects of habitat heterogeneity and other clustering processes on spatial distributions of tree species, Ecology, 94, 2436-2443.
  40. Jalilian, A., Guan, Y. and Waagepetersen, R. (2013) Decomposition of variance for spatial Cox processes, Scandinavian Journal of Statistics, 40, 119-137.
  41. Waagepetersen, R. and Guan, Y. (2009) Two-step estimation for inhomogeneous spatial point processes (revised July 24, 2008) and a simulation study, Journal of the Royal Statistical Society, Series B, 71, 685-702.
  42. Illian, J. B., Møller, J. and Waagepetersen, R. (2009) Hierarchic spatial point process analysis for a plant community with high biodiversity (revised 28.02.07), Environmental and Ecological Statistics, 16, 389-405.
  43. Guan, Y., Waagepetersen, R. and Beale, C. (2008) Second-order analysis of inhomogeneous spatial point processes with proportional intensity functions, Journal of the American Statistical Association, 103, 769-777.
  44. Waagepetersen, R. (2008) Estimating functions for inhomogeneous spatial point processes with incomplete covariate data (revised 28.05.2007), Biometrika, 95, 351-363.
  45. Møller, J. and Waagepetersen, R. (2007) Modern statistics for spatial point processes, Scandinavian Journal of Statistics, 34, 643-684.
  46. Waagepetersen, R. (2007) An estimating function approach to inference for inhomogeneous Neyman-Scott processes with Appendix (revised 21.03.06), Biometrics, 63, 252-258.
  47. Waagepetersen, R. and Schweder, T. (2006) Likelihood-based analysis of clustered line transect data (revised 13/09/2005), Journal of Agricultural, Biological, and Environmental Statistics, 11, 264-279.
  48. Waagepetersen, R. (2005) Discussion of "Residual analysis for spatial point processes", Journal of the Royal Statistical Society B, 67, 662.
  49. Benes, V., Bodlak, K., Møller, J. and Waagepetersen, R. (2005) A case study on point process modelling in disease mapping, Image Analysis and Stereology, 24, 159-168.
  50. Waagepetersen, R. (2004) Convergence of posteriors for discretized LGCPs, Statistics and Probability Letters, 66, 229-235.
  51. Baddeley, A. J., Møller, J. and Waagepetersen, R. (2000) Non- and semi-parametric estimation of interaction in inhomogeneous point patterns, Statistica Neerlandica, 54, 329-350.
  52. Møller, J., Syversveen, A.-R. and Waagepetersen, R. (1998) Log Gaussian Cox processes, Scandinavian Journal of Statistics, 25, 451-482.

Quantitative genetics

  1. Ibanez-Escriche, N., Sorensen, D. Waagepetersen, R. and Blasco, A. (2008) Selection for environmental variation: a statistical analysis and power calculations to detect response, Genetics, 180, 2209-2226.
  2. Ros, M., Sorensen, D., Waagepetersen, R., Dupont-Nivet, M., SanCristobal, M., Bonnet, J-C. and Mallard, J. (2004) Evidence for genetic control of adult weight plasticity in the snail Helix aspersa, Genetics, 168, 2089-2097.
  3. Sorensen, D. and Waagepetersen, R. (2003) Normal linear models with genetically structured residual variance heterogeneity: A case study, Genetical Research, 82, 207-222.

Generalized linear mixed models (MCMC, applications in agriculture and model assessment)

  1. Waagepetersen, R. (2006) A simulation-based goodness-of-fit test for random effects in generalized linear mixed models (revised 16/01/2006), Scandinavian Journal of Statistics, 33, 721-731.
  2. Christensen, O. F. and Waagepetersen, R. (2002) Bayesian prediction of spatial count data using generalised linear mixed models, Biometrics, 58, 280-286.
  3. Christensen, O. F, Møller, J. and Waagepetersen, R. (2001) Geometric ergodicity of Metropolis-Hastings algorithms for conditional simulation in generalised linear mixed models, Methodology and Computation in Applied Probability, 3, 309-327.

Spatial statistics (geostatistics and image analysis)

  1. Tøgersen, F. Aa. and Waagepetersen, R. (2004) Statistical modelling and deconvolution of yield meter data (post script)(pdf), Scandinavian Journal of Statistics, 31, 247-264.
  2. Møller, J. and Waagepetersen, R. (1999) Discussion on the paper 'Bayesian analysis of agricultural field experiments' by J. E. Besag and D. Higdon, J. Roy. Statist. Soc. B, 61, 735.
  3. Møller, J. and Waagepetersen, R. (1998) Markov connected component fields, Advances of Applied Probability, 30, 1-35.

Markov chain Monte Carlo

  1. Waagepetersen, R., Ibanez-Escriche, N. and Sorensen, D. (2008) A comparison of strategies for Markov chain Monte Carlo computation in quantitative genetics, Genetics, Selection, Evolution, 40, 161-176.
  2. Döge, G., Mecke, K., Møller, J., Stoyan, D. and Waagepetersen, R. (2004) Grand canonical simulations of hard-disk systems by simulated tempering, International Journal of Modern Physics C, 15, 1-19.
  3. Mase, S., Møller, J., Stoyan, D., Waagepetersen, R. and Döge, G. (2001) Packing densities and simulated tempering for hard core Gibbs point processes, Annals of the Institute of Statistical Mathematics, 53, 661-680.
  4. Waagepetersen, R. and Sorensen, Daniel (2001) A tutorial on reversible jump MCMC with a view toward QTL-mapping, International Statistical Review, 69, 49-61.

Applications in medicine, education and other fields

  1. Højbjerre-Frandsen, E., Jeppesen, M. L., Jensen, R. K., Dethlefsen, C. and Waagepetersen, R. (2024) A tutorial on using prognostic covariate adjustment for linear models to gain power in RCTs, submitted.
  2. Tao, K., Jensen, I. T., Zhang, S., Villa-Rodriguez, E., Blahovska, Z., Salomonsen, C. L., Martyn, A., Bjorgvinsdottir, T.N., Kelly, S., Janss, L., Glasius, M., Waagepetersen, R. and Radutoiu, S. (2023) Nitrogen source and nod factor signaling map out the assemblies of Lotus Japonicus root bacterial communities, Nature Communications, 15, 3426.
  3. Jensen, I. T., Janss, L., Radutoiu, S. and Waagepetersen, R. (2023) Compositionally aware estimation of cross-correlations for microbiome data, PLoS One, 19, e0305032.
  4. Rasmussen, J., Skejø, S. and Waagepetersen, R. (2023) Predicting tissue loads in running from inertial measurement units, Sensors, 23, 9836.
  5. Pedersen, P. L., Bjerre, M., Sunde, P.B., Aunio, P.A. and Waagepetersen, R. (2022) Differences in high- and low-performing students' fraction proficiency development, Journal of Experimental Education, 91, 636-654.
  6. Brund, R.B.K., Waagepetersen, R., Nielsen, R.O., Rasmussen, J., Nielsen, M.S., Andersen, C.H. and de Zee, M. (2021) How precisely can accessible variables predict Achilles and patellar tendon forces during running ?, Sensors (special issue on Sensor Technology for Sports Science), 21, 7418.
  7. Rasmussen, J., Waagepetersen, R. and Rasmussen, K. P. (2018) A new method for projection of anthropometric correlation for virtual population modeling, International Journal of Human Factors Modelling and Simulation, 6, 16-30.
  8. Andersen, S., Waagepetersen, R. and Laurberg, Peter (2015) Misclassification of iodine intake level from morning spot urine samples with high iodine excretion among Inuit and non-Inuit in Greenland, British Journal of Nutrition, 113, 1433-1440.
  9. Kurande, V. H., Bilgrau, A. E., Waagepetersen, R., Toft, E. and Prasad, R. (2013) Interrater reliability of diagnostic methods in traditional Indian Ayurvedic medicine, Evidence-based Complementary and Alternative Medicine, Volume 2013, Article ID 658275, 12 pages.
  10. Kurande, V. H., Waagepetersen, R., Toft, E. & Prasad, R. (2013) Reliability Studies of Diagnostic Methods in Indian Traditional Ayurveda Medicine - an Overview, Journal of Ayurveda and Integrative Medicine, 4, 67-76.
  11. Rodrigo-Domingo, M., Waagepetersen, R., Bødker, J.S., Falgreen, S., Kjeldsen, M.K., Johnsen, H.E., Dybkær, K. and Bøgsted, M. (2013) Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor, Briefings in Bioinformatics, 15, 519-533.
  12. Kurande, V., Waagepetersen, R., Toft, E. and Prasad, R. (2012) Reliability of pulse diagnosis in traditional Indian Ayurveda medicine, Global Advances in Health and Medicine, 1, 36-42.
  13. Waagepetersen, R. (2010) A statistical modeling approach to build expert credit risk rating systems, Journal of Credit Risk, 6, 81-94.
  14. Agerholm, N., Waagepetersen, R., Tradisauskas, N., Lahrmann, H. and Harms, L. (2008) Preliminary results from the intelligent speed adaptation project `Pay as you speed', Intelligent Transport Systems, 2, 143-153.
  15. Bertelsen, M.G., Tustin, D.S. and Waagepetersen, R. (2002) Effects of GA3 and GA4+7 on early bud development of "Pacific Rose", Journal of Horticultural Science and Biotechnology, 77, 83-90.

Book chapters:

  1. Møller, J. and Waagepetersen, R. (2003) An introduction to simulation-based inference for spatial point processes, in Spatial statistics and computational methods, Møller, J. (editor), Lecture Notes in Statistics 173, Springer-Verlag.
  2. Møller, J. and Waagepetersen, R. (2002) Statistical inference for Cox processes, in Spatial cluster modelling, Denison, D. and Lawson, A. B. (eds), Chapman and Hall/CRC.

Conference proceedings:

  1. Jensen, N. F., Hansen, T. K., Svane, A. M., Morelli, M. and Waagepetersen, R. (2023) Climate data for moisture simulations: producing a Danish moisture reference year and comparison with previously used reference year locations, NSB 2023 - 13th Nordic Symposium on Building Physics, Aalborg, Denmark, June 12-14, 2023.
  2. Hansen, P., Waagepetersen, R., Svane, A.M., Sporring, J., Stephensen, H., Hasselholt, S. and Sommer, S. (2021) Currents and K-functions for Fiber Point Processes, GSI 2021.
  3. Pedersen, P. L. and Waagepetersen, R. (2021) Natural-number bias pattern in answers to different fraction tasks. Proceedings of Norma 20 - The ninth Nordic Conference on Mathematics Education Oslo, 2021, 193-200.
  4. Rasmussen, J., Enemark M. L. and Waagepetersen, R. (2020) Data-based parametric biomechanical models for cyclic motions, 6th International Digital Human Modeling Symposium (DHM2020), Skövde, August 31 - September 2, 2020.
  5. Sporring, J., Waagepetersen, R. and Sommer, S. (2019) Generalizations of Ripley's $K$-function with application to space curves, Information Processing in Medical Imaging, Springer International Publishing. arXiv:1812.06870.
  6. Khanmohammadi, M., Waagepetersen, R., Nava, N., Nyengaard, J. and Sporring, J. (2014) Analysing the distribution of synaptic vesicles using a spatial point process model, Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, Association for Computing Machinery, 73-78.
  7. Kurande, V. H., Waagepetersen, R., Toft, E. and Prasad, R. (2013) Reliability of Pulse Diagnosis in Traditional Indian Ayurveda Medicine, Research in Complemetary Medicine/Forschende Komplementärmedizin: Research Practice Perspectives - Wissenschaft Praxis Perspektiven, 20 (Suppl 1), 86-87.
  8. Kurande, V. H.; Waagepetersen, R. and Toft, E. (2012) Repeatability of pulse diagnosis in traditional Indian Ayurveda medicine, BMC Complementary and Alternative Medicine, 12 (Suppl 1), 188, P02.132.
  9. Agerholm, N., Waagepetersen, R., Tradisauskas, N. and Lahrmann, H. (2008) Intelligent speed adaptation in company vehicles, Proceedings of the 2008 IEEE Intelligent Vehicles Symposium, Eindhoven University of Technology, Eindhoven, June 4-6, 936-943.
  10. Verification of a Probabilistic Model for A Distribution System with Integration of Dispersed Generation (2008) Chen, P., Chen, Z., Bak-Jensen, B., Waagepetersen, R., and Sørensen, S., Proceedings of the 16th Power Systems Computation Conference. Glasgow: University of Strathclyde, 7.
  11. Waagepetersen, R. (2006) Estimating functions for inhomogeneous Cox processes, Proceedings of S4G, the 6th International conference on Stereology, Spatial Statistics and Stochastic Geometry, Prague, Czech Republic, June 26-29, 2006, 149-158.
  12. Waagepetersen, R., Ibanez, N. and Sorensen, D. (2006) Strategies for MCMC computation in quantitative genetics, Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, August 13-18, 2006.
  13. Gianola, D., Sorensen, D. and Waagepetersen, R. (2003) Model choice in animal breeding: A case study of litter size in pigs. Joint Statistical Meetings of American Statistical Association, Institute of Mathematical Statistics, In: Abstract book, International Biometrics Society and Statistical Society of Canada. San Franciso, CA, USA, 31 July-7 August, 309.
  14. Benes, V., Bodlak, K., Møller, J. and Waagepetersen, R. (2003) Application of log Gaussian Cox processes in disease mapping, Proceedings of the ISI Conference on Environmental Statistics and Health, Santiago de Compostela, eds J. Mateu, D. Holland, and W. Gonzales-Mantiega, 95-105.
  15. Sorensen, D. and R. Waagepetersen (2002) Model selection for prediction of breeding values, Proceedings of the 7th World Congress of Genetics Applied to Livestock Production, Montpellier, France. Vol. 32, 513-520 (invited paper).
  16. Møller, J., Syversveen, A.-R. and Waagepetersen, R. (1997) Log Gaussian Cox processes: A statistical model for analyzing stand structural heterogeneity, Proceedings of First European Conference for Information Technology in Agriculture (editors Kure, H., Thysen, I., and Kristensen, A. R.), Department of Mathematics and Physics, The Royal Veterinary and Agricultural University, Denmark, 1997, 339-342.

Teaching material:

  1. Waagepetersen, R. (2006) An introduction to statistics for spatial point processes, handouts for one day course at Aalborg University, June 10, 2006.
  2. Waagepetersen, R. (2003) Hand outs and exercises for DINA Workshop on Monte Carlo methods for hierarchical models, October 30-31 2003.
  3. Lundbye-Christensen, S. and Waagepetersen, R. (2002) Exercises for the DINA Research School workshop on Data series, state-space models, and the Kalman filter.
  4. Waagepetersen, R. (1998) A quick introduction to Markov chain Monte Carlo (revised October 2003). Internal Report 8, Biometry Research Unit, Danish Institute of Agricultural Sciences (lecture notes for the DINA Research School).

Technical reports:

  1. Waagepetersen, R. and Guan, Y. (2008) Two-step estimation for inhomogeneous spatial point processes - a simulation study.
  2. Waagepetersen, R. (2007) A note on asymptotic results for estimating functions.
  3. Waagepetersen, R. (2005) Propriety of posteriors for Poisson processes.
  4. Benes, Viktor, Bodlak, K., Møller, J. and Waagepetersen, R. (2002) Spatial modelling of tick-borne encephalitis data. 24 pages.
  5. Christensen, O. F, Møller, J., and Waagepetersen, R. (2000) Analysis of spatial data using generalized linear mixed models and Langevin-type Markov chain Monte Carlo. R-002009, Department of Mathematics, Aalborg University. 25 pages.
  6. Waagepetersen, R. (1998) Kirsebær: et eksempel på anvendelse af generaliserede lineære modeller. Internal Report 9, Biometry Research Unit, Danish Institute of Agricultural Sciences.
  7. Waagepetersen, R. (1997) Contributions to the statistical modelling of image data and spatial point patterns. (Survey paper for Ph.D.-thesis). 56 pages.
  8. Waagepetersen, R. (1997) Analysis of residuals from segmentation of noisy images. Research Report 380, Dept. of Theoretical Statistics, University of Aarhus.
  9. Waagepetersen, R. (1997) Phase transition and simulation for a penalized Ising model with applications in Bayesian image analysis. Research Report 381, Dept. of Theoretical Statistics, University of Aarhus.
  10. Waagepetersen, R. (1995) Some aspects of geostatistics. 27 pages.
  11. Waagepetersen, R. (1994) Modelleringen af geologisk variabilitet i et grundvandshydraulisk perspektiv. Published in the DGU Data Documentation series. In danish. 54 pages.

Thesis:

My Ph.D.-thesis is constituted by the survey paper "Contributions to the statistical modelling of image data and spatial point patterns" together with the papers "Log Gaussian Cox processes", "Markov connected component fields", "Analysis of residuals from segmentation of noisy images", and "Phase transition and simulation for a penalized Ising model with applications in Bayesian image analysis".

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