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Asmussen, S., Jensen, J. L. & Rojas-Nandayapa, L. (2014). Exponential Family Techniques for the Lognormal Left Tail. T.N. Thiele Centre, Department of Mathematics, Aarhus University. Thiele Research Reports No. 01 http://math.au.dk/publs?publid=1010

Christensen, K., Oomen, R. & Podolskij, M. (2014). Fact or friction: Jumps at ultra high frequency. Journal of Financial Economics, 114(3), 576-599. https://doi.org/10.1016/j.jfineco.2014.07.007

Maia, R. P., Ask, B., Madsen, P., Pedersen, J. & Labouriau, R. (2014). Genetic determination of mortality rate in Danish dairy cows: a multivariate competing risk analysis based on the number of survived lactations. Journal of Dairy Science, 97(3), 1753-1761. https://doi.org/10.3168/jds.2013-6959

Feragen, A., Nielsen, M., Jensen, E. B. V., du Plessis, A. & Lauze, F. (2014). Geometry and Statistics: Manifolds and Stratified Spaces. Journal of Mathematical Imaging and Vision, 50(1-2), 1-4. https://doi.org/10.1007/s10851-014-0504-5

Penner, R., Andersen, E. S., Jensen, J. L., Kantcheva, A. K., Bublitz, M., Nissen, P., Rasmussen, A. M. H., Svane, K. L., Hammer, B., Rezazadegan, R., Nielsen, N. C., Nielsen, J. T. & Andersen, J. E. (2014). Hydrogen bond rotations as a uniform structural tool for analyzing protein architecture. Nature Communications, 5, Article 5803. https://doi.org/10.1038/ncomms6803

Asmussen, S. (2014). Lévy processes, phase-type distributions, and martingales. Stochastic Models, 30(4), 443-468. https://doi.org/10.1080/15326349.2014.958424

Podolskij, M., Schmidt, C. & Ziegel, J. (2014). Limit theorems for nondegenerate U-statistics of continuous semimartingales. Annals of Applied Probability, 24(6), 2491-2526. https://doi.org/10.1214/13-AAP983

Jensen, E. B. V. & Ziegel, J. F. (2014). Local stereology of tensors of convex bodies. Methodology and Computing in Applied Probability, 16(2), 263-282. https://doi.org/10.1007/s11009-013-9337-8

Hobolth, A. & Jensen, J. L. (2014). Markovian approximation to the finite loci coalescent with recombination along multiple sequences. Theoretical Population Biology, 98, 48-58. https://doi.org/10.1016/j.tpb.2014.01.002

Theil, P. K., Flummer, C., Hurley, W. L., Kristensen, N. B., Labouriau, R. & Sørensen, M. T. (2014). Mechanistic model to predict colostrum intake based on deuterium oxide dilution technique data and impact of gestation and prefarrowing diets on piglet intake and sow yield of colostrum. Journal of Animal Science, 92(12), 5507-5519. https://doi.org/10.2527/jas.2014-7841

Pimentel Maia, R., Madsen, P. & Labouriau, R. (2014). Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits. Journal of Applied Statistics, 41(6), 1286-1306. https://doi.org/10.1080/02664763.2013.868416

Asmussen, S. & Foss, S. (2014). On exceedance times for some processes with dependent increments. Journal of Applied Probability, 51(1), 136-151. https://doi.org/10.1239/jap/1395771419

Bak, B. A. & Jensen, J. L. (2014, May 23). On oracle efficiency of the ROAD classification rule. http://arxiv.org/abs/1405.5989

Heinrich, C. & Podolskij, M. (2014). On spectral distribution of high dimensional covariation matrices. Institut for Økonomi, Aarhus Universitet. CREATES Research Paper No. 2014-54

Barndorff-Nielsen, O. E., Benth, F. E., Pedersen, J. & Veraart, A. E. D. (2014). On stochastic integration for volatility modulated Lévy-driven Volterra processes. Stochastic Processes and Their Applications, 124(1), 812-847. https://doi.org/10.1016/j.spa.2013.09.007

Haagerup, U. & Thorbjørnsen, S. (2014). On the free Gamma distributions. Indiana University Mathematics Journal, 63(4), 1159-1194. https://doi.org/10.1512/iumj.2014.63.5288

Jensen, E. B. V. & Rasmusson, A. (2014). Rotational integral geometry and local stereology - with a view to image analysis. In V. Schmidt (Ed.), Stochastic Geometry, Spatial Statistics and Random Fields: Models and Algorithms (pp. 233-255). Springer Publishing Company. https://doi.org/10.1007/978-3-319-10064-7_8

Hobolth, A. & Jeff, T. (2014). Sampling and summary statistics of endpoint-conditioned paths in DNA sequence evolution. In M.-H. Chen, L. Kuo & P. O. Lewis (Eds.), Bayesian Phylogenetics: Methods, Algorithms, and Applications (1 ed., Vol. 1). CRC Press.

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

Nam, K., Munch, K., Hobolth, A., Y. Dutheil, J., Veeramah, K., Woerner, A., F. Hammer, M., Ape Genome Diversity Project, G., Mailund, T. & H. Schierup, M. (2014). Strong selective sweeps associated with ampliconic regions in great ape X chromosomes. arXiv.

Kousholt, A., Kiderlen, M. & Hug, D. (2014). Surface tensor estimation from linear sections. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports No. 07 http://math.au.dk/publs?publid=1004

Rønn-Nielsen, A. & Jensen, E. B. V. (2014). Tail asymptotics for the supremum of an infinitely divisible field with convolution equivalent Lévy measure. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports No. 09 http://math.au.dk/publs?publid=1006

Fissler, T. & Podolskij, M. (2014). Testing the maximal rank of the volatility process for continuous diffusions observed with noise. Institut for Økonomi, Aarhus Universitet. CREATES Research Paper No. 2014-52

Thórisdóttir, Ó. & Kiderlen, M. (2014). The Invariator Principle in Convex Geometry. Advances in Applied Mathematics, 58, 63-87. https://doi.org/10.1016/j.aam.2014.02.003

Prokesová, M., Dvorák, J. & Jensen, E. B. V. (2014). Two-step estimation procedures for inhomogeneous shot-noise Cox processes. Centre for Stochastic Geometry and Advanced Bioimaging, Aarhus University. CSGB Research Reports No. 02 http://math.au.dk/publs?publid=997

Andersen, I. T., Hahn, U. & Jensen, E. B. V. (2014). Vanishing auxiliary variables in PPS sampling - with applications in microscopy. Centre for Stochastic Geometry and Advanced Bioimaging, Aarhus University. CSGB Research Reports Vol. 2014 No. 01 http://data.imf.au.dk/publications/csgb/2014/math-csgb-2014-01.pdf

Tataru, P., Sand, A., Hobolth, A., Mailund, T. & Pedersen, C. N. S. (2013). Algorithms for Hidden Markov Models Restricted to Occurrences of Regular Expressions. Biology, 2(4), 1282-1295. https://doi.org/10.3390/biology2041282

Prokesová, M. & Jensen, E. B. V. (2013). Asymptotic Palm likelihood theory for stationary point processes. Annals of the Institute of Statistical Mathematics, 65(2), 387-412. https://doi.org/10.1007/s10463-012-0376-7

Corcuera, J. M., Hedevang, E., Pakkanen, M. S. & Podolskij, M. (2013). Asymptotic theory for Brownian semi-stationary processes with application to turbulence. Stochastic Processes and Their Applications, 123(7), 2552-2574. https://doi.org/10.1016/j.spa.2013.03.011

Jacod, J. & Podolskij, M. (2013). A test for the rank of the volatility process: The random perturbation approach. Annals of Statistics, 41(5), 2391-2427. https://doi.org/10.1214/13-AOS1153

Basse-O'Connor, A. & Rosiński, J. (2013). Characterization of the finite variation property for a class of stationary increment infinitely divisible processes. Stochastic Processes and Their Applications, 123(6), 1871-1890. https://doi.org/10.1016/j.spa.2013.01.014

Podolskij, M. & Yoshida, N. (2013). Edgeworth expansion for functionals of continuous diffusion processes. Institut for Økonomi, Aarhus Universitet. CREATES Research Paper No. 2013-33

Asmussen, S. & Kortschak, D. (2013). Error rates and improved algorithms for rare event simulation with heavy Weibull tails. T.N. Thiele Centre, Department of Mathematics, Aarhus University. Thiele Research Reports No. 02

Thórisdóttir, Ó., H.Rafati, A. & Kiderlen, M. (2013). Estimating the surface area of non-convex particles from central planar sections. Centre for Stochastic Geometry and Advanced Bioimaging, Aarhus University. CSGB Research Reports No. 08 http://math.au.dk/publs?publid=987

Sevón-Aimonen, M.-L., Labouriau, R., Maia, R. P., Haltia, S. & Uimari, P. (2013). Estimation of variance components of sow longevity traits using discrete time model. In Book of Abstracts of the 64th Annual Meeting of the European Association for Animal Production (2013 ed., Vol. 19, pp. 390). Wageningen Academic Publishers. http://www.eaap.org/Previous_Annual_Meetings/2013Nantes/Nantes_2013_Abstracts.pdf

Hahn, U. (2013). fdnonpar: an R package for statistical analysis of multivariate or functional data.. Computer programme, R-Forge. https://r-forge.r-project.org/R/?group_id=1763

Maia, R. P., Madsen, P., Pedersen, J. & Labouriau, R. (2013). Genetic study of mortality rate in Danish dairy cows: a multivariate competing risk analysis. In Book of Abstracts of the 64th Annual Meeting of the European Association for Animal Production (2013 ed., Vol. 19, pp. 315). Wageningen Academic Publishers. http://www.eaap.org/Previous_Annual_Meetings/2013Nantes/Nantes_2013_Abstracts.pdf

Maia, R. P., Madsen, P., Pedersen, J. & Labouriau, R. (2013). Genetic study of mortality rate in Danish dairy cows: a multivariate competing risk analysis. Poster session presented at 64th Annual Meeting of the European Federation of Anmal Science, Nantes, France. http://www.eaap.org/Previous_Annual_Meetings/2013Nantes/Nantes_2013_Abstracts.pdf

Podolskij, M. & Wasmuth, K. (2013). Goodness-of-fit testing for fractional diffusions. Statistical Inference for Stochastic Processes, 16(2), 147-159. https://doi.org/10.1007/s11203-013-9082-1

Prado-Martinez, J., Sudmant, P. H., Kidd, J. M., Li, H., Kelley, J. L., Lorente-Galdos, B., Veeramah, K. R., Woerner, A. E., O'Connor, T. D., Santpere, G., Cagan, A., Theunert, C., Casals, F., Laayouni, H., Munch, K., Hobolth, A., Halager, A. E., Malig, M., Hernandez-Rodriguez, J. ... Marques-Bonet, T. (2013). Great ape genetic diversity and population history. Nature, 499, 471–475. https://doi.org/10.1038/nature12228

Keller, K. K., Andersen, I. T., Andersen, J. B., Hahn, U., Stengaard-Pedersen, K., Hauge, E. M. & Nyengaard, J. R. (2013). Improving efficiency in stereology: a study applying the proportionator and the autodisector on virtual slides. Journal of Microscopy, 251(1), 68-76. https://doi.org/10.1111/jmi.12044

Hahn, U. & Jensen, E. B. V. (2013). Inhomogeneous spatial point processes with hidden second-order stationarity. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports Vol. 2013 No. 07 http://math.au.dk/publs?publid=985

Andersen, K. & Jensen, A. N. (2013). Intersection cuts for mixed integer conic quadratic sets. In M. Goemans & J. Correa (Eds.), 16th International IPCO Conference, Proceedings (pp. 37-48). Springer. https://doi.org/10.1007/978-3-642-36694-9_4

Kiderlen, M. (2013). Introduction into integral geometry and stereology. In E. Spodarev (Ed.), Stochastic geometry, spatial statistics and random fields: Asymptotic methods (pp. 21-48). Springer. https://doi.org/10.1007/978-3-642-33305-7_2

Kiderlen, M. & Kampf, J. (2013). Large Parallel Volumes of Finite and Compact Sets in d-Dimensional Euclidean Space. Documenta Mathematica, 18, 275-295. http://www.math.uni-bielefeld.de/documenta/vol-18/09.html

Elkjær, K., Labouriau, R., Ancker, M.-L., Gustafsson, H. & Callesen, H. (2013). Large-scale study on effects of metritis on reproduction in Danish Holstein cows. Journal of Dairy Science, 96(1), 372-377. https://doi.org/10.3168/jds.2012-5584

Jónsdóttir, K. Ý. & Jensen, E. B. V. (2013). Lévy-based error prediction in circular systematic sampling. Image Analysis and Stereology, 32(2), 117-125. https://doi.org/10.5566/ias.v32.p117-125

Jónsdóttir, K. Ý., Rønn-Nielsen, A., Mouridsen, K. & Jensen, E. B. V. (2013). Lévy-based modelling in brain imaging. Scandinavian Journal of Statistics, 40(3), 511-529. https://doi.org/10.1002/sjos.12000

Barndorff-Nielsen, O. E., Pérez-Abreu, V. & Thorbjørnsen, S. (2013). Levy Mixing. Alea, X(2), 1013-1062. http://alea.impa.br/articles/v10/10-41.pdf

Barndorff-Nielsen, O. E., Corcuera, J. M. & Podolskij, M. (2013). Limit theorems for functionals of higher order differences of Brownian semi-stationary processes. In A. N. Shiryaev, S. R. S. Varadhan & E. L. Presman (Eds.), Prokhorov and contemporary probability theory: In Honor of Yuri V. Prokhorov (pp. 69-96). Springer. https://doi.org/10.1007/978-3-642-33549-5_4

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Lars Madsen