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2014

Working Paper

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

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

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

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

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

2014

Contribution to conference

Madsen, P., Jensen, J., Labouriau, R., Christensen, O. F. & Sahana, G. (2014). DMU - A Package for Analyzing Multivariate Mixed Models in quantitative Genetics and Genomics. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014#/activity/5tSDu1wL58

Madsen, P., Jensen, J., Labouriau, R., Christensen, O. F. & Sahana, G. (2014). DMU - A Package for Analyzing Multivariate Mixed Models in quantitative Genetics and Genomics. Poster session presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada. https://event.crowdcompass.com/wcgalp2014#/activity/5tSDu1wL58

2014

Contribution to book anthology

Shah, R., Hirsch, C., Kroese, D. P. & Schmidt, V. (2014). Rare event probability estimation for connectivity of large random graphs. In Proceedings of the Winter Simulation Conference 2014 (pp. 510-521)

Asmussen, S., Lipsky, L. & Thompson, S. (2014). Checkpointing in failure recovery in computing and data transmission. In B. Sericola, M. Telek & G. Horváth (Eds.), Analytical and Stochastic Modeling Techniques and Applications (pp. 253-272). Springer. https://doi.org/10.1007/978-3-319-08219-6_18

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.

2014

Contribution to journal

Thórisdóttir, Ó., H.Rafati, A. & Kiderlen, M. (2014). Estimating the surface area of nonconvex particles from central planar sections. Journal of Microscopy, 255(1), 49–64. https://doi.org/10.1111/jmi.12136

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

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

Stenzel, O., Hirsch, C., Brereton, T., Baumeier, B., Andrienko, D., Kroese, D. & Schmidt, V. (2014). A general framework for consistent estimation of charge transport properties via random walks in random environments. Multiscale modeling simulation, 12(3), 1108-1134.

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

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

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

Neuhäuser, D., Hirsch, C., Gloaguen, C. & Schmidt, V. (2014). Ratio limits and simulation algorithms for the Palm version of stationary iterated tessellations. Journal of Statistical Computation and Simulation, 84(7), 1486-1504.

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

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

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

Greilich, S., Hahn, U., Kiderlen, M., Andersen, C. E. & Bassler, N. (2014). Efficient calculation of local dose distributions for response modeling in proton and heavier ion beams. The European Physical Journal D: Atomic, Molecular, Optical and Plasma Physics, 68(217), Article 327. https://doi.org/10.1140/epjd/e2014-40825-0

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

Corcuera, J. M., Nualart, D. & Podolskij, M. (2014). Asymptotics of weighted random sums. Communications in Applied and Industrial Mathematics, 6(1), Article e-486. https://doi.org/10.1685/journal.caim.486

Christiansen, M. C., Hirsch, C. & Schmidt, V. (2014). Prediction of regionalized car insurance risks based on control variates. Statistics Risk Modeling, 31(2), 163-181.

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

Brereton, T., Hirsch, C., Schmidt, V. & Kroese, D. (2014). A critical exponent for shortest-path scaling in continuum percolation. Journal of Physics A: Mathematical and Theoretical, 47(50), 505003.

Baudoin, F., Bonnefont, M. & Garofalo, N. (2014). A sub-Riemannian curvature-dimension inequality, volume doubling property and the Poincaré inequality. Mathematische Annalen, 358(3-4), 833-860. https://doi.org/10.1007/s00208-013-0961-y

Baudoin, F. & Wang, J. (2014). Curvature Dimension Inequalities and Subelliptic Heat Kernel Gradient Bounds on Contact Manifolds. Potential Analysis, 40(2), 163-193. https://doi.org/10.1007/s11118-013-9345-x

Baudoin, F. & Kim, B. (2014). Sobolev, Poincaré, and isoperimetric inequalities for subelliptic diffusion operators satisfying a generalized curvature dimension inequality. Revista Matematica Iberoamericana, 30(1), 109-131. https://doi.org/10.4171/rmi/771

Baudoin, F. & Wang, J. (2014). The Subelliptic Heat Kernels of the Quaternionic Hopf Fibration. Potential Analysis, 41(3), 959-982. https://doi.org/10.1007/s11118-014-9403-z

Baudoin, F., Ouyang, C. & Tindel, S. (2014). Upper bounds for the density of solutions to stochastic differential equations driven by fractional Brownian motions. Annales de l'institut Henri Poincare (B) Probability and Statistics, 50(1), 111-135. https://doi.org/10.1214/12-AIHP522

Baudoin, F., Bonnefont, M., Garofalo, N. & Munive, I. H. (2014). Volume and distance comparison theorems for sub-Riemannian manifolds. Journal of Functional Analysis, 267(7), 2005-2027. https://doi.org/10.1016/j.jfa.2014.07.030

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

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

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

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

Andersen, L. N., Mailund, T. & Hobolth, A. (2014). Efficient computation in the IM model. Journal of Mathematical Biology, 68(6), 1423-1451. https://doi.org/10.1007/s00285-013-0671-9

2013

Working Paper

Pimentel Maia, R., Madsen, P. & Labouriau, R. (2013). Multivariate Survival Mixed Models for Genetic Analysis of Longevity Traits. (pp. 1-36). ArXiv. http://arxiv.org/abs/1303.0810

2013

Non textual

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

Hahn, U. (2013). plutils: an R package for plotting with style. Computer programme, R-Forge. https://r-forge.r-project.org/R/?group_id=1763

Hahn, U. (2013). sostatpp: an R-package for analysis of hidden second-order stationary point processes. Computer programme, R-Forge. https://r-forge.r-project.org/R/?group_id=1763

2013

Working Paper

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

Thórisdóttir, Ó. & Kiderlen, M. (2013). The invariator principle in convex geometry. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports No. 06 http://math.au.dk/publs?publid=982

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

Kiderlen, M. & Hörig, M. (2013). Matérn's hard core models of types I and II with arbitrary compact grains. Centre for Stochastic Geometry and advanced Bioimaging, Aarhus University. CSGB Research Reports No. 05 http://math.au.dk/publs?publid=980

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

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

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Lars Madsen