Publikationer via PURE

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Barndorff-Nielsen, O. E., Gupta, V. K., Pérez-Abreu, V. & Waymire, E. (red.) (1998). Stochastic methods in hydrology: rain, landforms and floods. CIMAT, Guanajuato, Mexico, 25-28 March 1996. World Scientific. Advanced Series on Statistical Science and Applied Probability Bind 7

Basse-O'Connor, A., Graversen, S.-E. & Pedersen, J. (2014). Stochastic integration on the real line. Theory of Probability and Its Applications, 58(2), 193-213. https://doi.org/10.1137/S0040585X97986540

Hoffmann-Jørgensen, J. (2003). Stochastic inequalities and perfect independence. I J. Hoffmann-Jørgensen, M. B. Marcus & J. A. Wellner (red.), High dimensional probability III (s. 3-34). Birkhäuser Verlag.

Barndorff-Nielsen, O. E., Kendall, W. S. & van Lieshout, M. N. M. (red.) (1998). Stochastic geometry: likelihood and computation. Chapman & Hall/CRC.

Schmiegel, J., Cleve, J., Eggers, H. C., Pearson, B. R. & Greiner, M. (2004). Stochastic energy-cascade model for (1+1)-dimensional fully developed turbulence. Phys. Lett. A, 320, 247-253.

Davis, R. A., Nielsen, M. S. & Rohde, V. U. (2020). Stochastic differential equations with a fractionally filtered delay: A semimartingale model for long-range dependent processes. Bernoulli, 26(2), 799-827. https://doi.org/10.3150/18-BEJ1086

Guneysu, B., Matte, O. & Møller, J. S. (2017). Stochastic differential equations for models of non-relativistic matter interacting with quantized radiation fields. Probability Theory and Related Fields, 167(3-4), 817-915. https://doi.org/10.1007/s00440-016-0694-4

Basse-O'Connor, A., Nielsen, M. S., Pedersen, J. & Rohde, V. U. (2020). Stochastic delay differential equations and related autoregressive models. Stochastics: An International Journal of Probability and Stochastic Processes , 92(3), 454-477. https://doi.org/10.1080/17442508.2019.1635601

Ivanovs, J. (2021). Stochastic decompositions in bivariate risk and queueing models with mutual assistance. Stochastic Models, 37(1), 5-22. https://doi.org/10.1080/15326349.2020.1760888

Barndorff-Nielsen, O. E., Jupp, P. E. & Kendall, W. S. (1994). Stochastic calculus, statistical asymptotics, Taylor strings and phyla. Annales de la Faculté des Sciences de Toulouse, 3(1), 5-62.

Güneysu, B., Matte, O. & Møller, J. S. (2014). Stochastic calculus and non-relativistic QED. I P. Exner, W. König & H. Niedhardt (red.), Mathematical Results in Quantum Mechanics: Proceedings of the QMATH12 Conference (s. 315-323). World Scientific. https://doi.org/10.1142/9789814618144_0027

Wray, K. B. (2020). Still Resisting: replies to my critics: K. Brad Wray: Resisting scientific realism, Cambridge University Press, 2018, 224 pp., $105 HB. Metascience, 29, 33-40. https://doi.org/10.1007/s11016-020-00490-7

Andersen, K. (1990). Stevin's Theory of Perspective: The Origin of a Dutch Academic Approach to Perspective. Tractrix, 2, 25-62.

Baddeley, A. & Jensen, E. B. V. (2005). Stereology for Statisticians. Chapman /.

Stehr, M. (2020). Stereology and Spatio-Temporal Models: Numerical Integration Methods for Volume Estimation and Extremes for Lévy-based Models. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Søndergaard, N., Nyengaard, J. R. & Bloch, S. L. (2020). Stereologic Investigation of Mastoid Air Cell Geometry: Volume, Surface Area, and Anisotropy. Otology and Neurotology, 41(5), e630-e637. https://doi.org/10.1097/MAO.0000000000002583

Dare, E. (2024). Stereologically adapted Crofton formulae for tensor valuations. Advances in Applied Mathematics, 160, Artikel 102754. https://doi.org/10.1016/j.aam.2024.102754

Jensen, E. B. V. (2021). Stereological inference on mean particle shape from vertical sections. Australian & New Zealand Journal of Statistics, 63(1), 6-18. https://doi.org/10.1111/anzs.12309

Ziegel, J. & Kiderlen, M. (2010). Stereological estimation of surface area from digital images. Image Analysis and Stereology, 29, 99-110. http://www.wise-t.com/ias/article.php?id=265&year=2010&issue=6

Larsen, N. Y., Ziegel, J. F., Nyengaard, J. R. & Jensen, E. B. V. (2019). Stereological estimation of particle shape from vertical sections. Journal of Microscopy, 275(3), 183-194. https://doi.org/10.1111/jmi.12826

H. Rafati, A., Ziegel, J., Nyengaard, J. R. & Jensen, E. B. V. (2015). Stereological Estimation of Particle Shape and Orientation From Volume Tensors. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports Nr. 12 http://math.au.dk/publs?publid=1050

Rafati, A. H., Ziegel, J., Nyengaard, J. R. & Jensen, E. B. V. (2016). Stereological estimation of particle shape and orientation from volume tensors. Journal of Microscopy, 263(3), 229-237. https://doi.org/10.1111/jmi.12382

Kousholt, A., Ziegel, J. F., Kiderlen, M. & Jensen, E. B. V. (2016). Stereological estimation of mean particle volume tensors in R3 from vertical sections. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports Bind 2016/09 http://math.au.dk/publs?publid=1073

Kousholt, A., Ziegel, J., Kiderlen, M. & Jensen, E. B. V. (2017). Stereological estimation of mean particle volume tensors in R3 from vertical sections. I E. B. V. Jensen & M. Kiderlen (red.), Tensor Valuations and Their Applications in Stochastic Geometry and Imaging (Bind 2177, s. 423-434). Springer.

Kousholt, A., Ziegel, J., Kiderlen, M. & Jensen, E. B. V. (2016). Stereological estimation of mean particle volume tensors in R³ from vertical sections. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports Nr. 09 http://csgb.dk/publications/csgbrr/2016/

Kieu, K. & Jensen, E. B. V. (1993). Stereological estimation based on isotropic slices through fixed points. Journal of Microscopy, 170(1), 45-51. https://doi.org/10.1111/j.1365-2818.1993.tb03322.x

Hansen, L. V. (2011). Stereological analysis of spatial structures. Department of Mathematical Sciences, Aarhus University.

Hobolth, A. & Jensen, E. B. V. (2002). Stereological analysis of shape. Image Analysis and Stereology, 21(4), S23-S29. https://doi.org/10.5566/ias.v21.pS23-S29

Jensen, E. B. V. (2009). Stereologi - at slutte fra 2 til 3 dimensioner. Villum Fonden. Årsskrift, 38-41. http://www.vkr-fondene.dk/Data/PropertyFile/423039/Dansk%20%C3%85rsskrift%202009.pdf

Meyer, M. K. K. & Stald, L. J. (2006). Stenos uopklarede mysterier. Aarhus Stiftstidende.

Sørensen, H. K. (2013). StenoMusen runder 60 numre. Stenomusen, 60.

Nielsen, K. H. & Zilhão, I. (2018). Stem Frenzy: teaching science to children and young people, 1815-1991. Cambridge Core Blog. http://blog.journals.cambridge.org/2018/09/07/stem-frenzy-teaching-science-to-children-and-young-people-1815-1991/

Jacobsen, A. L. L. (2010). Steam trawling on the south-east continental shelf of Australia. An environmental history of fishing, management and science in NSW, 1865 -1961.

Kragh, H. (1993). Steady state theory. I Encyclopedia of Cosmology: Historical, Philosophical and Scientific Foundations of Modern Cosmology (s. 629-636). Garland Science.

Asmussen, S. & Rubinstein, R. Y. (1995). Steady state rare events simulation in queueing models and its complexity properties. I J. H. Dshalalow (red.), Advances in queueing theory, methods, and open problems (s. 429-466). CRC Press.

Kragh, H. (1999). Steady State Cosmology and General Relativity: Reconciliation or Conflict? I H. Goenner, J. Renn & J. Ritter (red.), The Expanding Worlds of General Relativity (s. 377-404). Birkhäuser Verlag.

Jensen, E. B. V. (2006). Statistisk billedanalyse - eller hvordan man kan analysere dynamiske rumlige data. Carlsbergfondet. Aarsskrift, 10-17.

Jensen, J. L. & Nielsen, M. B. (2016). Statistik og databehandling (Kemi): Teoretiske øvelser.

Jensen, J. L. (2012). Statistik: viden fra data. Aarhus Universitetsforlag.

Nielsen, K. H. (2018). Statistik. Weekendavisen, Sektion 4 (Ideer), 10.

Barndorff-Nielsen, O. E. & Jupp, P. E. (1997). Statistics, yokes and symplectic geometry. Annales de la Faculté des Sciences de Toulouse, 6(3), 389-427.

Blæsild, P. & Granfeldt, J. (2003). Statistics with Applications in Biology and Geology. Chapman /.

Prokesova, M., Hahn, U. & Jensen, E. B. V. (2006). Statistics for locally scaled point processes. I A. Baddeley, P. Gregori, J. Mateu, R. Stoica & D. Stoyan (red.), Case Studies in Spatial Point Process Modelling (s. 99-123). Springer. https://doi.org/10.1007/0-387-31144-0_5

Andersen, H. (2010). Statisticians and historians should help improve metrics. Nature, 464(7293), 1267-1267. https://doi.org/10.1038/4641267a

Barndorff-Nielsen, O. E. & Jupp, P. E. (1999). Statistical (Taylor) string theory. I Encyclopedia of statistical sciences (Bind Update vol.3, s. 701-704). John Wiley & Sons Ltd.

Hobolth, A. (2002). Statistical shape analysis of featureless objects. Department of Mathematical Sciences, Aarhus University.

Jensen, J. L. & Hobolth, A. (2005). Statistical inference in evolutionary models of DNA sequences via the EM algorithm. Statistical Applications in Genetics and Molecular Biology, 4(1), article18.

Jensen, E. B. V. & Nielsen, L. S. (2004). Statistical inference for transformation inhomogeneous point processes. Scandinavian Journal of Statistics, 31(1), 131-142. https://doi.org/10.1111/j.1467-9469.2004.00377.x

Tiepner, A. (2024). Statistical inference for stochastic partial differential equations from local measurements. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Andersen, I. T. (2016). Statistical Inference for Microscopy Data – Efficient Sampling and Modelling by Spatial Point Processes. Department of Mathematics, Aarhus University.

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Lars Madsen