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Svane, A. M. & Vedel Jensen, E. B. (2017). Rotational Crofton formulae for Minkowski tensors and some affine counterparts. Advances in Applied Mathematics, 91, 44-75. https://doi.org/10.1016/j.aam.2017.05.009

Kiderlen, M. & Jensen, E. B. V. (2017). Rotation Invariant Valuations. In E. B. V. Jensen & M. Kiderlen (Eds.), Tensor Valuations and Their Applications in Stochastic Geometry and Imaging (Vol. 2177 , pp. 185-212). Springer. https://doi.org/10.1007/978-3-319-51951-7_7

Madsen, T., Hobolth, A., Jensen, J. L. & Pedersen, J. S. (2017). Significance evaluation in factor graphs. BMC Bioinformatics , 18(1), 199. Article 199. https://doi.org/10.1186/s12859-017-1614-z

Tataru, P., Simonsen, M., Bataillon, T. & Hobolth, A. (2017). Statistical Inference in the Wright–Fisher Model Using Allele Frequency Data. Systematic Biology, 66(1), e30-e46. https://doi.org/10.1093/sysbio/syw056

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

Baudoin, F. (2017). Stochastic analysis on Sub-Riemannian manifolds with transverse symmetries. Annals of Probability, 45(1), 56-81. https://doi.org/10.1214/14-AOP964

Baudoin, F. & Wang, J. (2017). Stochastic areas, winding numbers and Hopf fibrations. Probability Theory and Related Fields, 169(3-4), 977-1005. https://doi.org/10.1007/s00440-016-0745-x

Asmussen, S., Hashorva, E., Laub, P. & Taimre, T. (2017). Tail asymptotics for light-tailed Weibull-like sums. Probability and Mathematical Statistics, 37(2), 235-256.

Asmussen, S., Hashorva, E., Laub, P. & Taimre, T. (2017). Tail asymptotics of light-tailed Weibull-like sums. (pp. 235-256). https://doi.org/10.19195/0208-4147.37.2.3

Asmussen, S., Hashorva, E., Laub, P. J. & Taimre, T. (2017). TAIL ASYMPTOTICS OF LIGHT-TAILED WEIBULL-LIKE SUMS. Probability and Mathematical Statistics, 37(2), 235-256.

Sørensen, C. K., Labouriau, R. & Hovmøller, M. S. (2017). Temporal and spatial variability of fungal structures and host responses in an incompatible Rust-Wheat interaction. Frontiers in Plant Science, 8, Article 484. https://doi.org/10.3389/fpls.2017.00484

Kiderlen, M. & Jensen, E. B. V. (Eds.) (2017). Tensor Valuations and Their Applications in Stochastic Geometry and Imaging. Springer. Lecture Notes in Mathematics Vol. 2177

Fissler, T. & Podolskij, M. (2017). Testing the maximal rank of the volatility process for continuous diffusions observed with noise. Bernoulli, 23(4B), 3021-3066. https://doi.org/10.3150/16-BEJ836

Kiderlen, M. & Dorph-Petersen, K. A. (2017). The Cavalieri estimator with unequal section spacing revisited. Image Analysis and Stereology, 36(2), 135-141. https://doi.org/10.5566/ias.1723

Kiderlen, M. & Dorph-Petersen, K.-A. (2017). The Cavalieri estimator with unequal section spacing revisited. http://csgb.dk/publications/csgbrr/2017/

Thorbjørnsen, S., Hasebe, T. & Sakuma, N. (2017). The normal distribution is freely selfdecomposable. International Mathematics Research Notices, 1-22.

Jensen, E. B. V. & Gundersen, H. J. G. (2017). THE WORKSHOPS ON STOCHASTIC GEOMETRY, STEREOLOGY AND IMAGE ANALYSIS. Image Analysis and Stereology, 36(3), 179-185. https://doi.org/10.5566/ias.1755

Asmussen, S., Ivanovs, J. & Rønn-Nielsen, A. (2017). Time inhomogeneity in longest gap and longest run problems. Stochastic Processes and Their Applications, 127(2), 574-589. https://doi.org/10.1016/j.spa.2016.06.018

Hirsch, C., Jahnel, B., Keeler, P. & Patterson, R. IA. (2017). Traffic flow densities in large transport networks. Advances in Applied Probability, 49(4), 1091-1115.

Prokešová, M., Dvořák, J. & Jensen, E. B. V. (2017). Two-step estimation procedures for inhomogeneous shot-noise Cox processes. Annals of the Institute of Statistical Mathematics, 69(3), 513-542. https://doi.org/10.1007/s10463-016-0556-y

Hug, D., Kiderlen, M. & Svane, A. M. (2017). Voronoi-Based Estimation of Minkowski Tensors from Finite Point Samples. Discrete & Computational Geometry, 57(3), 545-570. https://doi.org/10.1007/s00454-016-9851-x

Jörnsten, K. & Klose, A. (2016). An improved Lagrangian relaxation and dual ascent approach to facility location problems. Computational Management Science, 13(3), 317-348. https://doi.org/10.1007/s10287-015-0244-z

Laub, P. J., Asmussen, S., Jensen, J. L. & Rojas-Nandayapa, L. (2016). Approximating the Laplace transform of the sum of dependent lognormals. Advances in Applied Probability, 48(A), 203-215. https://doi.org/10.1017/apr.2016.50

Hinrichsen, L. K., Riber, A. B. & Labouriau, R. (2016). Associations between and development of welfare indicators in organic layers. Animal, 10(6), 953-960. https://doi.org/10.1017/S1751731115003018

Neuhäuser, D., Hirsch, C., Gloaguen, C. & Schmidt, V. (2016). A stochastic model for multi-hierarchical networks. Methodology and Computing in Applied Probability, 18(4), 1129-1151.

Podolskij, M. & Thamrongrat, N. (2016). A weak limit theorem for numerical approximation of Brownian semi-stationary processes. In F. E. Benth & G. Di Nunno (Eds.), Stochastics of Environmental and Financial Economics (pp. 101-120). Springer. https://doi.org/10.1007/978-3-319-23425-0_4

Hirsch, C. (2016). Bounded-hop percolation and wireless communication. Journal of Applied Probability, 53(3), 833-845.

Christensen, S. T. & Kiderlen, M. (2016). Comparison of two global digital algorithms for Minkowski tensor estimation. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports Vol. 2016/10 http://math.au.dk/publs?publid=1074

Asmussen, S. & Lehtomaa, J. V. (2016). Distinguishing log-concavity from heavy tails. Thiele Centre, Institut for Matematiske Fag, Aarhus Universitet. Thiele Research Reports Vol. 6, 2016 http://math.au.dk/forskning/publikationer/instituttets-serier/publication/publid/1090/

Podolskij, M. & Yoshida, N. (2016). Edgeworth expansion for functionals of continuous diffusion processes. Annals of Applied Probability, 26(6), 3415-3455. https://doi.org/10.1214/16-AAP1179

Rønn-Nielsen, A., Sporring, J. & Jensen, E. B. V. (2016). Estimation of sample spacing in stochastic processes. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports Vol. 17, 2016 http://math.au.dk/forskning/publikationer/instituttets-serier/publication/publid/1091/

Lebovits, J. & Podolskij, M. (2016). Estimation of the global regularity of a multifractional Brownian motion. Institut for Økonomi, Aarhus Universitet. CREATES Research Paper No. 2016-33

Strauch, C. (2016). Exact adaptive pointwise drift estimation for multidimensional ergodic diffusions. Prob. Theory Rel. Fields, 164(1-2), 361-400.

Rønn-Nielsen, A. & Jensen, E. B. V. (2016). Excursion sets of infinitely divisible random fields with convolution equivalent Lévy measure. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports Vol. 2016/11 http://math.au.dk/publs?publid=1075

Asmussen, S., Jensen, J. L. & Rojas-Nandayapa, L. (2016). Exponential Family Techniques for the Lognormal Left Tail. Scandinavian Journal of Statistics, 43(3), 774-787. https://doi.org/10.1111/sjos.12203

Hinrichsen, L. K., Labouriau, R., Engberg, R. M., Knierim, U. & Sørensen, J. T. (2016). Helminth infection is associated with hen mortality in Danish organic egg production. Veterinary Record, 179(8), article 196. https://doi.org/10.1136/vr.103614

Hahn, U. & Jensen, E. B. V. (2016). Hidden Second-order Stationary Spatial Point Processes. Scandinavian Journal of Statistics, 43(2), 455-475. https://doi.org/10.1111/sjos.12185

Bak, B. A. & Jensen, J. L. (2016). High dimensional classifiers in the imbalanced case. Computational Statistics & Data Analysis, 98, 46-59. https://doi.org/10.1016/j.csda.2015.12.009

Nielsen, S., Simonsen, S. & Hobolth, A. (2016). Inferring Population Genetic Parameters: Particle Filtering, HMM, Ripley’s K-Function or Runs of Homozygosity? In M. Frith & C. Nørgaard Storm Pedersen (Eds.), Algorithms in Bioinformatics - 16th International Workshop, WABI 2016, Proceedings (Vol. 9838, pp. 234-245). Springer. https://doi.org/10.1007/978-3-319-43681-4_19

Thomsen, R., Edwards, S. A., Rousing, T., Labouriau, R. & Sørensen, J. T. (2016). Influence of social mixing and group size on skin lesions and mounting in organic entire male pigs. Animal, 10(7), 1225-1233. https://doi.org/10.1017/S1751731116000069

Hirsch, C., Jahnel, B., Keeler, P. & Patterson, R. IA. (2016). Large deviation principles for connectable receivers in wireless networks. Advances in Applied Probability, 48(4), 1061-1094.

Thompson, S., Lipsky, L. & Asmussen, S. (2016). Linear algebraic methods in RESTART problems in Markovian systems. In L. Fiondella & A. Puliafito (Eds.), Principles of Performance and Reliability Modeling and Evaluation: Essays in Honor of Kishor Trivedi on his 70th Birthday (Vol. Part 3, pp. 449-479). Springer. https://doi.org/10.1007/978-3-319-30599-8_17

Asmussen, S. & Thøgersen, J. (2016). Markov Dependence in Renewal Equations and Random Sums with Heavy Tails. Thiele Centre, Institut for Matematiske Fag, Aarhus Universitet. Thiele Research Reports Vol. 2, 2016 http://math.au.dk/forskning/publikationer/instituttets-serier/publication/publid/1071/

Andersen, I. T. & Hahn, U. (2016). Matérn thinned Cox processes. Spatial Statistics, 15, 1-21. https://doi.org/10.1016/j.spasta.2015.10.005

Hirsch, C., Neuhäuser, D. & Schmidt, V. (2016). Moderate deviations for shortest-path lengths on random segment processes. ESAIM: Probability and Statistics, 20, 261-292.

Mrkvička, T., Soubeyrand, S., Myllymäki, M., Grabarnik, P. & Hahn, U. (2016). Monte Carlo testing in spatial statistics, with applications to spatial residuals. Spatial Statistics, 18(A), 40-53. https://doi.org/10.1016/j.spasta.2016.04.005

Nielsen, M. M., Tataru, P., Madsen, T., Hobolth, A. & Pedersen, J. S. (2016). Motif discovery in ranked lists of sequences. (pp. 1-4). http://biorxiv.org/content/biorxiv/suppl/2016/01/11/035956.DC2/035956-1.pdf

Labouriau, R. (2016). Multivariate Generalized Linear Mixed Models with High Complexity / Modèles linéaires généralisés mixtes multivariés avec complexité élevée. Abstract from 44th Annual Meeting of the Statistical Society of Canada, Canada.

Baudoin, F., Nualart, E., Ouyang, C. & Tindel, S. (2016). On probability laws of solutions to differential systems driven by a fractional Brownian motion. Annals of Probability, 44(4), 2554-2590. https://doi.org/10.1214/15-AOP1028

Hirsch, C. (2016). On the absence of percolation in a line-segment based lilypond model. In Annales de l'Institut Henri Poincaré, Probabilités et Statistiques (Vol. 52, pp. 127-145)

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Lars Madsen