Articles
- Schlather, M. and Stehlík, M. (2026). Martin Schlather and Milan Stehlík’s contribution to the discussion of ‘Statistical exploration of the manifold hypothesis’ by N. Whiteley et al.. Journal of the Royal Statistical Society. Series B, Statistical Methodolgy, 88, 423–424.
- Schlather, M. and Stehlík, M. (2026). Milan Stehlík and Martin Schlather’s contribution to the discussion of ‘Statistical exploration of the manifold hypothesis’ by Whiteley et al.. Journal of the Royal Statistical Society. Series B, Statistical Methodolgy, 88, 425–426.
- Schlather, A. and Schlather, M. (2025). Depicting falsifiability in algebraic modelling. J : Multidisciplinary Scientific Journal, 8, 1–23.
- Brehmer, J. R., Gneiting, T., Herrmann, M., Marzocchi, W., Schlather, M. and Strokorb, K. (2024). Comparative evaluation of point process forecasts. Annals of the Institute of Statistical Mathematics : AISM, 76, 47–71.
- Schlather, M. and Ditscheid, C. (2024). An intrinsic Characterization of Shannon’s and Rényi’s entropy. Entropy, 26, 1–17.
- Dörr, C. and Schlather, M. (2023). Characterization theorems for pseudo cross-variograms. Journal of Applied Probability, 60, 1219-1231.
- Dörr, C. and Schlather, M. (2023). Covariance models for multivariate random fields resulting from pseudo cross-variograms. Journal of Multivariate Analysis : JMVA, 197, 1–13.
- Freudenberg, A., Schlather, M., Vandenplas, J. and Pook, T. (2023). Accelerating single-step evaluations through GPU offloading. Interbull Bulletin, 59, 23–32.
- 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.
- Moreva, O. and Schlather, M. (2023). Bivariate covariance functions of Pólya type. Journal of Multivariate Analysis : JMVA, 194, 1–15.
- 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. Annals of the Institute of Statistical Mathematics : AISM, 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.
- Schlather, M., Freudenberg, A., Moerkotte, G., Pook, T. and Vandenplas, J. (2023). Software project “miraculix”: Efficient computations with large genomic datasets. In , Proceedings of the 2023 Interbull Meeting, Lyon, France, 26–27 August 2023 (S. 15–22). Interbull Bulletin, Swedish University of Agricultural Sciences (SLU): Uppsala.
- 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