Photo credit: Anna Logue
Articles
- Freudenberg, A., Vandenplas, J., Schlather, M., Pook, T., Evans, R. and Napel, J. . (2023). Accelerated matrix-vector multiplications for matrices involving genotype covariates with applications in genomic prediction. Frontiers in Genetics, 14, 1–9.
- Küster, S., Haverkamp, L., Schlather, M. and Traulsen, I. (2023). An approach towards a practicable assessment of neonatal piglet body core temperature using automatic object detection based on thermal images. Agriculture, 13, 1–17.
- Li, Y., Schlather, M. and Erdfelder, E. (2023). A queueing model of visual search. Journal of Mathematical Psychology, 115, 1–22.
- Pook, T., Reimer, C., Freudenberg, A., Büttgen, L., Geibel, J., Ganesan, A., Ha, N.-T., Schlather, M., Mikkelsen, L. F. and Simianer, H. (2021). The Modular Breeding Program Simulator (MoBPS) allows efficient simulation of complex breeding programs. Animal Production Science, 61, 1982-1989.
- Dirrler, M., Dörr, C. and Schlather, M. (2020). A generalization of Matérn hard-core processes with applications to max-stable processes. Journal of Applied Probability, 57, 1298-1312.
- Pook, T., Schlather, M. and Simianer, H. (2020). MoBPS – Modular Breeding Program Simulator. G3: Genes, Genomes, Genetics, 10, 1915-1918.
- Oesting, M., Schlather, M. and Schillings, C. (2019). Sampling sup-normalized spectral functions for Brown–Resnick processes. Stat : the ISI's Journal for the Rapid Dissemination of Statistics Research, 8, 1–11.
- Pook, T., Schlather, M., Campos, G. . ., Mayer, M., Schoen, C. C. and Simianer, H. (2019). HaploBlocker: Creation of subgroup-specific haplotype blocks and libraries. Genetics, 212, 1045-1061.
- Schreck, N., Piepho, H.-P. and Schlather, M. (2019). Best prediction of the additive genomic variance in random-effects models. Genetics, 213, 379–394.
- Moreva, O. and Schlather, M. (2018). Fast and exact simulation of univariate and bivariate Gaussian random fields. Stat : the ISI's Journal for the Rapid Dissemination of Statistics Research, 7, 1–14.
- Oesting, M., Schlather, M. and Zhou, C. (2018). Exact and fast simulation of max-stable processes on a compact set using the normalized spectral representation. Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability, 24, 1497-1530.
- Reimer, C., Rubin, C.-J., Sharifi, A. R., Ha, N.-T., Weigend, S., Waldmann, K.-H., Distl, O., Pant, S. D., Fredholm, M., Schlather, M. and Simianer, H. (2018). Analysis of porcine body size variation using re-sequencing data of miniature and large pigs. BMC Genomics, 19, 1–17.
- Fiebig, U.-R., Strokorb, K. and Schlather, M. (2017). The realization problem for tail correlation functions. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 20, 121–168.
- Ha, N.-T., Gross, J. J., Sharifi, A. R., Schlather, M., Drögemüller, C., Schnyder, U., Schmitz-Hsu, F., Bruckmaier, R. and Simianer, H. (2017). Genetische Analyse der metabolischen Adaptation von Milchkühen in der Frühlaktation. Züchtungskunde, 89, 48–60.
- Ha, N.-T., Sharifi, A. R., Heise, J., Schlather, M., Schnyder, U., Gross, J. J., Schmitz-Hsu, F., Bruckmaier, R. and Simianer, H. (2017). A reaction norm sire model to study the effect of metabolic challenge in early lactation on the functional longevity of dairy cows. Journal of Dairy Science : JDS, 100, 3742-3753.
- Hewer, R., Friederichs, P., Hense, A. and Schlather, M. (2017). A matèrn-based multivariate gaussian random process for a consistent model of the horizontal wind components and relates variables. Journal of the Atmospheric Sciences, 74, 3833-3845.
- Kolb, O., Döring, L., Klinger, M., Schlather, M. and Schmidt, M. U. (2017). Individualisierte Tutorien im Mathematikstudium. Neues Handbuch Hochschullehre, 82, 77–88.
- Oesting, M., Schlather, M. and Friederichs, P. (2017). Statistical post-processing of forecasts for extremes using bivariate Brown-Resnick processes with an application to wind gusts. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 20, 309–332.
- Schlather, M. and Moreva, O. (2017). A parametric variogram model bridging between bounded and unbounded variogram. Wiley Interdisciplinary Reviews : WIREs. Cognitive Science, 6, 47–52.
- Lang, A., Potthoff, J., Schlather, M. and Schwab, D. (2016). Continuity of random fields on Riemannian manifolds. Communications on Stochastic Analysis, 10, 185–193.
- Malinowski, A., Schlather, M. and Zhang, Z. (2016). Intrinsically weighted means and non-ergodic marked point processes. The Annals of Statistics, 68, 1–24.
- Martini, J. W. R., Schlather, M. and Schütz, S. (2016). A model for carrier-mediated biological signal transduction based on equilibrium ligand binding theory. Bulletin of Mathematical Biology, 78, 1039-1057.
- Berger, S., Schlather, M., Campos, G. . ., Weigend, S., Preisinger, R., Erbe, M. and Simianer, H. (2015). A scale-corrected comparison of linkage disequilibrium levels between genic and non-genic regions. PLOS ONE, 10, 1–19.
- Ehlert, A., Fiebig, U.-R., Janßen, A. and Schlather, M. (2015). Joint extremal behavior of hidden and observable time series with applications to GARCH processes. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 18, 109–140.
- Engelke, S., Kabluchko, Z. and Schlather, M. (2015). Maxima of independent non-identically distributed Gaussian vectors. Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability, 21, 38–61.
- Engelke, S., Malinowski, A., Kabluchko, Z. and Schlather, M. (2015). Estimation of Hüsler-Reiss distributions and Brown-Resnick processes. Journal of the Royal Statistical Society. Series B, Statistical Methodolgy, 77, 239–265.
- Ha, N.-T., Gross, J. J., von Dorland, A., Tetens, J., Thaller, G., Schlather, M., Bruckmaier, R. and Simianer, H. (2015). Gene-based mapping and pathway analysis of 2 metabolic traits in dairy cows. PLOS ONE, 10, 1–15.
- Malinowski, A., Schlather, M. and Zhang, Z. (2015). Marked point process adjusted tail dependence analysis for high-frequency financial data. Statistics and its interface, 8, 109–122.
- Ober, U., Huang, W., Magwire, M., Schlather, M., Simianer, H. and Mackay, T. F. C. (2015). Accounting for genetic architecture improves sequence based genomic prediciton for a Drosophila fitness trait. PLOS ONE, 10, 1–17.
- Schlather, M., Malinowski, A., Menck, P. J., Oesting, M. and Strokorb, K. (2015). Analysis, simulation and prediction of multivariate random fields with package randomfields. Journal of Statistical Software, 63, 1–25.
- Strokorb, K., Ballani, F. and Schlather, M. (2015). Tail correlation functions of max-stable processes: Construction principles, recovery and diversity of some mixing max-stable processes with identical TCF. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 18, 241–271.
- Strokorb, K. and Schlather, M. (2015). An exceptional max-stable process fully parameterized by its extremal coefficients. Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability, 21, 276–302.
- Engelke, S., Malinowski, A., Oesting, M. and Schlather, M. (2014). Statistical inference for max-stable processes by conditioning on extreme events. Advances in Applied Probability, 46, 478–495.
- Freytag, S., Manitz, J., Schlather, M., Kneib, T., Amos, C. I., Risch, A., Chang-Claude, J., Heinrich, J. and Bickeböller, H. (2014). A network-based kernel machine test for identification of risk pathways in genome-wide association studies. Human Heredity, 76, 64–75.
- Manitz, J., Kneib, T., Schlather, M., Helbing, D. and Brockmann, D. (2014). Origin detecion durin food-borne disease outbreaks – a case study of the 2011 EHEC/
HUS outbreak in Germany. PLoS Currents, 6, 1–31. - Martini, J. W. R., Habeck, M. and Schlather, M. (2014). A derivation of the grand canonical partition function for systems with a finite number of binding sites using a Markov-chain model for the dynamics of single molecules. Journal of Mathematical Chemistry, 52, 665–674.
- Oesting, M. and Schlather, M. (2014). Conditional Sampling for max-stable processes with a mixed moving maxima representation. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 17, 157–192.
- Martini, J. W. R., Schlather, M. and Ullmann, G. M. (2013). On the interaction of different types of ligands binding to the same molecule Part I: the transfer of the decoupled sites representation. Journal of Mathematical Chemistry, 51, 672–695.
- Martini, J. W. R., Schlather, M. and Ullmann, G. M. (2013). On the interaction of different types of ligands binding to the same molecule Part II: Systems with n to 2 and n to 3 binding sites. Journal of Mathematical Chemistry, 51, 696–714.
- Martini, J. W. R., Ullmann, G. M. and Schlather, M. (2013). The meaning of the decoupled sites representation in terms of statistical mechanics and stochastics. Match : communications in mathematical and in computer chemistry, 70, 829–850.
- Scheuerer, M., Schaback, R. and Schlather, M. (2013). Interpolation of spatial data – a stochastic or a deterministic problem? European Journal of Applied Mathematics, 24, 601–629.
- Ballani, F., Kabluchko, Z. and Schlather, M. (2012). Random Marked Sets. Advances in Applied Probability, 44, 603–616.
- Freytag, S., Bickeböller, H., Amos, C. I., Kneib, T. and Schlather, M. (2012). A Novel Kernel for Correcting Size Bias in the Logistic Kernel Machine Test with an Application to Rheumatoid Arthritis. Human Heredity, 74, 97–108.
- Ober, U., Ayroles, J. F., Stone, E. A., Richards, S., Zhu, D., Gibbs, R. A., Stricker, C., Gianola, D., Schlather, M., Mackay, T. F. C. and Simianer, H. (2012). Using Whole-Genome Sequence Data to Predict Quantitative Trait Phenotypes in Drosophila melanogaster. PLoS Genetics, 8, 1–14.
- Oesting, M., Kabluchko, Z. and Schlather, M. (2012). Simulation of Brown-Resnick Processes. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 15, 89–107.
- Scheuerer, M. and Schlather, M. (2012). Covariance Models for Divergence-Free and Curl-Free Random Vector Fields. Stochastic Models, 28, 433–451.
- Ballani, F. and Schlather, M. (2011). A construction principle for multivariate extreme value distributions. Biometrika, 98, 633–645.
- Engelke, S., Kabluchko, Z. and Schlather, M. (2011). An equivalent representation of the Brown-Resnick process. Statistics & Probability Letters, 81, 1150-1154.
- Ober, U., Erbe, M., Long, N., Porcu, E., Schlather, M. and Simianer, H. (2011). Predicting genetic values : a kernel-based best linear unbiased prediction with genomic data. Genetics, 188, 695–708.
- Fasen, V., Klüppelberg, C. and Schlather, M. (2010). High-level dependence in time series models. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 13, 1–33.
- Gneiting, T., Kleiber, W. and Schlather, M. (2010). Matérn cross-covariance functions for multivariate random fields. Journal of the American Statistical Association : JASA, 105, 1167-1177.
- Kabluchko, Z. and Schlather, M. (2010). Ergodic properties of max-infinitely divisible processes. Stochastic Processes and Their Applications, 120, 281–295.
- Schlather, M. (2010). Some covariance models based on normal scale mixtures. Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability, 16, 780–797.
- Kabluchko, Z., Schlather, M. and de Haan, L. (2009). Stationary max-stable fields associated to negative definite functions. The Annals of Probability, 37, 2042–2065.
- Bogner, C., Wolf, B., Schlather, M. and Huwe, B. (2008). Analysing flow patterns from dye tracer experiments in a forest soil using extreme value statistics. European Journal of Soil Science : EJSS, 59, 103–113.
- Ehlert, A. and Schlather, M. (2008). Capturing the multivariate extremal index: Bounds and interconnections. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 11, 353–377.
- Perrin, O. and Schlather, M. (2007). Can any multivariate Gaussian vector be interpreted as a sample from a stationary random process? Statistics & Probability Letters, 77, 881–884.
- Gneiting, T., Sevcíková, H., Percival, D. B., Schlather, M. and Jiang, Y. (2006). Fast and Exact Simulation of Large Gaussian Lattice Systems in R^2: Exploring the Limits. Journal of Computational & Graphical Statistics, 15, 483–501.
- Schlather, M. and Gneiting, T. (2006). Local approximation of variograms by covariance functions. Statistics & Probability Letters, 76, 1303-1304.
- Schlather, M. and Huwe, B. (2005). A risk index for characterising flow pattern in soils using dye tracer distributions. Journal of Contaminant Hydrology, 79, 25–44.
- Schlather, M. and Huwe, B. (2005). A stochastic model for 3-dimensional flow patterns in infiltration experiments. Journal of Hydrology, 310, 17–27.
- Gneiting, T. and Schlather, M. (2004). Stochastic models that separate fractal dimension and the Hurst effect. SIAM Review, 46, 269–282.
- Schlather, M. and Huwe, B. (2004). The use of the language interface of R: two examples for modelling water flux and solute transport. Computers & Geosciences : CAGEO, 30, 197–201.
- Schlather, M., Ribeiro, P. J. and Diggle, P. J. (2004). Detecting dependence between marks and locations of marked point processes. Journal of the Royal Statistical Society. Series B, Statistical Methodolgy, 66, 79–93.
- Huwe, B., Schlather, M. and Mertens, M. (2003). Nutzerfreundliche Programme zur Modellierung des Stickstoffhaushalts und des Wasser- und Lösungstransports. Mitteilungen der Deutschen Bodenkundlichen Gesellschaft, 102, 87–88.
- Schlather, M. and Huwe, B. (2003). Ein Ansatz zur Charakterisierung des Gefährdungspotenzials bei Böden. Mitteilungen der Deutschen Bodenkundlichen Gesellschaft, 102, 125–126.
- Schlather, M. and Tawn, J. A. (2003). A dependence measure for multivariate and spatial extreme values: properties and inference. Biometrika, 90, 139–156.
- Schlather, M. (2002). Characterisation of point processes with Gaussian marks independent of locations. Mathematische Nachrichten, 239, 204–214.
- Schlather, M. (2002). Models for stationary max-stable random fields. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 5, 33–44.
- Schlather, M. and Tawn, J. A. (2002). Inequalities for the extremal coefficients of multivariate extreme value distributions. Extremes : Statistical Theory and Applications in Science, Engineering and Economics, 5, 87–102.
- Gneiting, T., Sasvári, Z. and Schlather, M. (2001). Analogies and correspondences between variograms and covariance functions. Advances in Applied Probability, 33, 617–630.
- Schlather, M. (2001). Examples for the coefficient of tail dependence and the domain of attraction of a bivariate extreme value distribution. Statistics & Probability Letters, 53, 325–329.
- Schlather, M. (2001). Limit distributions of norms of vectors of positive i.i.d. random variables. The Annals of Probability, 29, 862–881.
- Schlather, M. (2001). On the second-order characteristics of marked point processes. Bernoulli : Official Journal of the Bernoulli Society for Mathematical Statistics and Probability, 7, 99–117.
- Schlather, M. (2001). Simulation and Analysis of Random Fields. R News / The R Project for Statistical Computing, 1, 18–20.
- Schlather, M. and Huwe, B. (2001). Skalenabhängigkeit von Invasionsperkolationsmodellen. Mitteilungen der Deutschen Bodenkundlichen Gesellschaft, 96, 117–118.
- Schlather, M. (2000). A formula for the edge length distribution function of the Poisson Voronoi tessellation. Mathematische Nachrichten, 214, 113–119.
- Schlather, M. (2000). On a class of models of stochastic geometry constructed by random measures. Mathematische Nachrichten, 213, 114–154.
- Stoyan, D. and Schlather, M. (2000). Random sequential adsorption: relationship to dead leaves and characterization of variability. Journal of Statistical Physics, 100, 969–979.
- Schlather, M. and Stoyan, D. (1999). Edge systems of time-dependent incomplete Poisson Voronoi tessellations. Stochastic Models, 15, 599–615.
- Brummer, B., von Cramon-Taubadel, S., Nivievskyi, O. and Schlather, M. (2010). Agglomeration economies in Ukrainian dairy sector: a marked point process approach. In , Proceedings of the 116th Symposium of the European Association of Agricultural Economists = Actes du 116. Séminaire de l'Association Européenne des Economistes Agricoles (S. 1–11). , Wissenschaftsverl. Vauk: Kiel.
- Ober, U., Erbe, M., Schlather, M. and Simianer, H. (2010). Kernel-based BLUP with genomic data. In , 9th World Congress on Genetics Applied to Livestock Production : proceedings; Leipzig, Germany; August 1–6,2010 (S. 0126-0129). , Ges. für Tierzuchtwissenschaften: Leipzig.
- Schlather, M. and Huwe, B. (2003). Ansätze zur Charakterisierung des Gefährdungspotenzials bei Wald- und Ackerböden. In , Tagungsband : 08.09. November 2002 am MIBEG-Institut Tübingen / Internationale Biometrische Gesellschaft Deutsche Region, AG Ökologie (S. 59–62). Tagungsberichte der Arbeitsgruppe Ökologie und Umwelt, Ges.: Tübingen.
- Schlather, M. and Huwe, B. (2000). Dynamisch induzierte Muster von Transportprozessen in Waldböden. In , Wasser-Gesteins-Wechselwirkungen : Kurzfassungen der Vorträge und Poster / HydroGeoEvent 2000, zugleich Fachtagung der Fachsektion Hydrogeologie in der Deutschen Geologischen Gesellschaft, Heidelberg, 29.9. bis 4.10.2000 (S. 124). Schriftenreihe / Deutsche Geologische Gesellschaft, Dt. Geologische Ges.: Hannover.
- Porcu, E., Montero, J. M. and Schlather, M. (eds.) (2012). Advances and challenges in space-time modelling of natural events. Berlin [u.a.]: Springer.
- Schlather, M. (2012). Construction of covariance functions and unconditional simulation of random fields. In Advances and Challenges in Space-time Modelling of Natural Events (S. 25–54). Berlin [u.a.]: Springer.
- Schlather, M. and Stoyan, D. (1997). The covariance of the Stienen model. In Proceedings of the International Symposium on Advances in Theory and Applications of Random Sets : Fontainebleau, France, 9–11 October 1996 (S. 157–174). Singapore [u.a.]: World Scientific.
- Gneiting, T. and Schlather, M. (2012). Space-time covariance models. In , Encyclopedia of Environmetrics (S. ). Chichester: Wiley & Sons.
- Gneiting, T. and Schlather, M. (2002). Space-time covariance models. In , Encyclopedia of Environmetrics (S. 2041–2045). Chichester [u.a.]: Wiley.
- Ober, U., Malinowski, A., Schlather, M. and Simianer, H. (2013). The expected linkage disequilibrium in finite populations revisited.
- Strokorb, K. and Schlather, M. (2012). Characterizing extremal coefficient functions and extremal correlation functions.
- Engelke, S. and Schlather, M. (2011). Rezension zu: Qian, Song S.: Environmental and Ecological Statistics with R. Boca Raton, Fla., 2010. Review, Biometrical Journal
- Malinowski, A. and Schlather, M. (2011). Rezension zu: Gentleman, Robert: R Programming for Bioinformatics. Boca Raton, Fla., 2009. Review, Biometrical Journal
- Schlather, M. (2009). Rezension zu: Bolker, Benjamin M.: Ecological Models and Data in R. Princeton, NJ, 2008. Review, Biometrical Journal
- Schlather, M. (2007). Rezension zu: Jacobsen, Martin: Point Process Theory and Applications. Berlin, 2006. Review, Journal of the American Statistical Association : JASA