Publications and reports of Rasmus Waagepetersen

Books:

• Møller, J. and Waagepetersen, R. (2003). Statistical inference and simulation for spatial point processes. Chapman and Hall/CRC Press.
  List of corrections and comments.

Journal publications (sorted by topic and publication date):

Theory and applications of spatial point processes

• Guan, Y., Jalilian, A. and Waagepetersen, R. (2011) Optimal estimation of the intensity function of spatial point process, submitted.
• Jalilian, A., Guan, Y. and Waagepetersen, R. (2011) Decomposition of variance for spatial Cox processes, Scandinavian Journal of Statistics, to appear.
• 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.
• 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.
• Waagepetersen, R. (2007). Estimating functions for inhomogeneous spatial point processes with incomplete covariate data (revised 28.05.2007), Biometrika, 95, 351-363.
• Illian, J. B., Møller, J. and Waagepetersen, R. (2007). Hierarchic spatial point process analysis for a plant community with high biodiversity (revised 28.02.07), Environmental and Ecological Statistics, 16, 389-405. DOI 10.1007/s10651-007-0070-8.
• Møller, J. and Waagepetersen, R. (2007). Modern statistics for spatial point processes, Scandinavian Journal of Statistics, 34, 643-684.
• Waagepetersen, R. (2007). An estimating function approach to inference for inhomogeneous Neyman-Scott processes with Appendix (revised 21.03.06), Biometrics, 63, 252-258.
• 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.
• Waagepetersen, R. (2005). Discussion of "Residual analysis for spatial point processes", Journal of the Royal Statistical Society B, 67, 662.
• 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.
• Waagepetersen, R. (2004). Convergence of posteriors for discretized LGCPs. Statistics and Probability Letters, 66, 229-235.
• 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.
• Møller, J., Syversveen, A.-R., and Waagepetersen, R. (1998). Log Gaussian Cox processes, Scandinavian Journal of Statistics, 25, 451-482.

Quantitative genetics

• 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.
• Ros, M., Sorensen, D., Waagepetersen, R., Dupont-Nivet, M., SanCristobal, M., Bonnet, J-C., Mallard, J. (2004). Evidence for genetic control of adult weight plasticity in the snail Helix aspersa. Genetics, 168, 2089-2097.
• 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)

• 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.
• Christensen, O. F. and Waagepetersen, R. (2002). Bayesian prediction of spatial count data using generalised linear mixed models. Biometrics, 58, 280-286.
• 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)

• 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.
• 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.
• Møller, J. and Waagepetersen, R. (1998). Markov connected component fields. Advances of Applied Probability, 30, 1-35.

Markov chain Monte Carlo

• 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.
• 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.
• 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.
• 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 agriculture, finance and engineering

• Waagepetersen, R. (2010). A statistical modeling approach to build expert credit risk rating systems, Journal of Credit Risk, 6, 81-94.
• 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.
• M. G. Bertelsen, D.S. Tustin, 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:

• 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.
• 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:

• Agerholm, N., Waagepetersen, R., Tradisauskas, N., Lahrmann, H. (2008). Intelligent speed adaptation in company vehicles, Proceedings of the 2008 IEEE Intelligent Vehicles Symposium p. 936-943, Eindhoven University of Technology, Eindhoven, June 4-6, 2008.
• Verification of a Probabilistic Model for A Distribution System with Integration of Dispersed Generation (2008) Chen, Peiyuan, Chen, Zhe, Bak-Jensen, Birgitte, Waagepetersen, Rasmus, and Sørensen, Stefan. I, Proceedings of the 16th Power Systems Computation Conference. Glasgow: University of Strathclyde, p. 7.
• 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, pages 149-158.
• 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.
• 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.
• Benes, V., Bodlak, K., Møller, J. and Waagepetersen, R. (2003). Application of log Gaussian Cox processes in disease mapping. In: Proceedings of the ISI Conference on Environmental Statistics and Health, Santiago de Compostela, eds J. Mateu, D. Holland, and W. Gonzales-Mantiega, 95-105.
• Sorensen, D. and R. Waagepetersen (2002). Model selection for prediction of breeding values. In: Proceedings of the 7th World Congress of Genetics Applied to Livestock Production, Montpellier, France. Vol. 32, 513-520 (invited paper).
• Møller, J., Syversveen, A.-R., and Waagepetersen, R. (1997). Log Gaussian Cox processes: A statistical model for analyzing stand structural heterogeneity. In 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:

• Waagepetersen, R. (2006) An introduction to statistics for spatial point processes, handouts for one day course at Aalborg University, June 10, 2006.
• Waagepetersen, R. (2003). Hand outs and exercises for DINA Workshop on Monte Carlo methods for hierarchical models, October 30-31 2003.
• Lundbye-Christensen, S. and Waagepetersen, R. (2002). Exercises for the DINA Research School workshop on Data series, state-space models, and the Kalman filter.
• 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:

• Waagepetersen, R. and Guan, Y. (2008). Two-step estimation for inhomogeneous spatial point processes - a simulation study.
• Waagepetersen, R. (2007). A note on asymptotic results for estimating functions.
• Waagepetersen, R. (2005). Propriety of posteriors for Poisson processes.
• Benes, Viktor, Bodlak, K., Møller, J. and Waagepetersen, R. (2002). Spatial modelling of tick-borne encephalitis data. 24 pages.
• 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.
• Waagepetersen, R. (1998). Kirsebær: et eksempel på anvendelse af generaliserede lineære modeller. Internal Report 9, Biometry Research Unit, Danish Institute of Agricultural Sciences.
• Waagepetersen, R. (1997). Contributions to the statistical modelling of image data and spatial point patterns. (Survey paper for Ph.D.-thesis). 56 pages.
• Waagepetersen, R. (1997). Analysis of residuals from segmentation of noisy images. Research Report 380, Dept. of Theoretical Statistics, University of Aarhus.
• 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.
• Waagepetersen, R. (1994). Modelleringen af geologisk variabilitet i et grundvandshydraulisk perspektiv. Published in the DGU Data Documentation series. In danish. 54 pages.

Thesis: