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Apart from a few exceptions for the class of extremal-t processes, existing literature mainly focuses on models with stationary dependence structures. In this paper, we propose a novel non-stationary approach that can be used for both Brown--Resnick and extremal-t processes -- two of the most popular classes of max-stable processes -- by including covariates in the corresponding variogram and correlation functions, respectively. While max-stable processes with deterministic covariates inherit most of the properties from classical max-stable processes, we additionally investigate theoretical properties of max-stable processes conditional on random covariates. We show that these can result in both asymptotically dependent and asymptotically independent processes. Thus, conditional models are more flexible than classical max-stable models. In numerical experiments, we study the finite-sample performance of pairwise likelihood estimators for the novel non-stationary models in both scenarios. Furthermore, we apply our approach to extreme precipitation data in two regions in Southern and Northern Germany and compare the results to existing stationary models in terms of Takeuchi's information criterion (TIC). Our results indicate that, for this case study, non-stationary models are more appropriate than stationary ones for the region in Southern Germany.", "issn" : "1572-915X", "doi" : "10.1007/s10687-025-00512-9", "bibtexKey": "Forster2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2315011045dbfe6991ff1263eb1577019/marcooesting", "tags" : [ "exc2075","myown","ourwork","pn5","pn5-10","updated" ], "intraHash" : "315011045dbfe6991ff1263eb1577019", "interHash" : "4aad88ea6dc492ba9597bb71a7aee4dc", "label" : "Bayesian inference for functional extreme events defined via partially unobserved processes", "user" : "marcooesting", "description" : "", "date" : "2026-01-01 19:50:23", "changeDate" : "2026-01-01 19:59:41", "count" : 4, "pub-type": "misc", "year": "2025", "url": "https://arxiv.org/abs/2512.24356", "author": [ "Max Thannheimer","Marco Oesting" ], "authors": [ {"first" : "Max", "last" : "Thannheimer"}, {"first" : "Marco", "last" : "Oesting"} ], "eprint" : "2512.24356", "archiveprefix" : "arXiv", "primaryclass" : "stat.ME", "bibtexKey": "thannheimer2025bayesianinferencefunctionalextreme" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2571ca45b777948ebb956e1270d687c14/marcooesting", "tags" : [ "exc2075","myown","ourwork","peerreviewed","pn5","pn5-10","updated" ], "intraHash" : "571ca45b777948ebb956e1270d687c14", "interHash" : "b8ace9af129cf666ee87414cfabacab6", "label" : "Evaluation of Binary Classifiers for Asymptotically Dependent and Independent Extremes", "user" : "marcooesting", "description" : "", "date" : "2026-01-01 19:45:58", "changeDate" : "2026-01-01 19:45:58", "count" : 5, "pub-type": "article", "journal": "Journal of the American Statistical Association","publisher":"Informa UK Limited", "year": "2025", "url": "http://dx.doi.org/10.1080/01621459.2025.2529024", "author": [ "Juliette Legrand","Philippe Naveau","Marco Oesting" ], "authors": [ {"first" : "Juliette", "last" : "Legrand"}, {"first" : "Philippe", "last" : "Naveau"}, {"first" : "Marco", "last" : "Oesting"} ], "volume": "120","number": "551","pages": "1558\u20131568", "issn" : "1537-274X", "doi" : "10.1080/01621459.2025.2529024", "bibtexKey": "Legrand_2025" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/23657ac3c0a4fa87616f908737d53e226/marcooesting", "tags" : [ "exc2075","myown","ourwork","pn5","pn5-10","preprint","updated" ], "intraHash" : "3657ac3c0a4fa87616f908737d53e226", "interHash" : "807aa68e3c64df2a015a366c9c3120eb", "label" : "Extremes in High Dimensions: Methods and Scalable Algorithms", "user" : "marcooesting", "description" : "", "date" : "2024-12-30 16:52:13", "changeDate" : "2024-12-30 16:52:13", "count" : 4, "pub-type": "misc", "year": "2024", "url": "https://arxiv.org/abs/2303.04258", "author": [ "Johannes Lederer","Marco Oesting" ], "authors": [ {"first" : "Johannes", "last" : "Lederer"}, {"first" : "Marco", "last" : "Oesting"} ], "eprint" : "2303.04258", "archiveprefix" : "arXiv", "primaryclass" : "stat.ME", "bibtexKey": "lederer2024extremeshighdimensionsmethods" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/27d5360d7c737e3ce987e385ac79cc245/marcooesting", "tags" : [ "exc2075","myown","ourwork","peerreviewed","pn5","pn5-10" ], "intraHash" : "7d5360d7c737e3ce987e385ac79cc245", "interHash" : "1917717d09db562e04dede966123a64b", "label" : "Estimation of the spectral measure from convex combinations of regularly varying random vectors", "user" : "marcooesting", "description" : "", "date" : "2024-12-30 16:48:12", "changeDate" : "2024-12-30 16:48:12", "count" : 5, "pub-type": "article", "journal": "The Annals of Statistics","publisher":"Institute of Mathematical Statistics", "year": "2024", "url": "https://doi.org/10.1214/24-AOS2387", "author": [ "Marco Oesting","Olivier Wintenberger" ], "authors": [ {"first" : "Marco", "last" : "Oesting"}, {"first" : "Olivier", "last" : "Wintenberger"} ], "volume": "52","number": "6","pages": "2529 -- 2556","abstract": "The extremal dependence structure of a regularly varying random vector X is fully described by its limiting spectral measure. In this paper, we investigate how to recover characteristics of the measure, such as extremal coefficients, from the extremal behaviour of convex combinations of components of X. Our considerations result in a class of new estimators of moments of the corresponding combinations for the spectral vector. We show asymptotic normality by means of a functional limit theorem and, focusing on the estimation of extremal coefficients, we verify that the minimal asymptotic variance can be achieved by a plug-in estimator using subsampling bootstrap. We illustrate the benefits of our approach on simulated and real data.", "doi" : "10.1214/24-AOS2387", "bibtexKey": "10.1214/24-AOS2387" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2e5a4d2169b8678158e964a4d11c98c90/marcooesting", "tags" : [ "myown","peerreviewed" ], "intraHash" : "e5a4d2169b8678158e964a4d11c98c90", "interHash" : "13012d3aa57c829709c0b5939ad0aa5d", "label" : "On the distribution of a max-stable process conditional on max-linear functionals", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 14:54:31", "changeDate" : "2024-12-30 17:02:37", "count" : 2, "pub-type": "article", "journal": "Statistics & Probability Letters","publisher":"Elsevier BV", "year": "2015", "url": "http://dx.doi.org/10.1016/j.spl.2015.02.002", "author": [ "Marco Oesting" ], "authors": [ {"first" : "Marco", "last" : "Oesting"} ], "volume": "100","pages": "158\u2013163", "issn" : "0167-7152", "doi" : "10.1016/j.spl.2015.02.002", "bibtexKey": "Oesting_2015" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2df3d6b25950371729a08cb9287fdf1e6/marcooesting", "tags" : [ "myown","peerreviewed" ], "intraHash" : "df3d6b25950371729a08cb9287fdf1e6", "interHash" : "f24b9768dfaa8fa08e3f77e09a5b4812", "label" : "Analysis, Simulation and Prediction of Multivariate Random Fields with PackageRandomFields", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 14:53:50", "changeDate" : "2023-12-14 14:53:50", "count" : 2, "pub-type": "article", "journal": "Journal of Statistical Software","publisher":"Foundation for Open Access Statistic", "year": "2015", "url": "http://dx.doi.org/10.18637/jss.v063.i08", "author": [ "Martin Schlather","Alexander Malinowski","Peter J. Menck","Marco Oesting","Kirstin Strokorb" ], "authors": [ {"first" : "Martin", "last" : "Schlather"}, {"first" : "Alexander", "last" : "Malinowski"}, {"first" : "Peter J.", "last" : "Menck"}, {"first" : "Marco", "last" : "Oesting"}, {"first" : "Kirstin", "last" : "Strokorb"} ], "volume": "63","number": "8", "issn" : "1548-7660", "doi" : "10.18637/jss.v063.i08", "bibtexKey": "Schlather_2015" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d52c47f4582996549b53af6cead93f88/marcooesting", "tags" : [ "myown","peerreviewed" ], "intraHash" : "d52c47f4582996549b53af6cead93f88", "interHash" : "aefa307a04a5364b24b4086f200b6c75", "label" : "Exact simulation of max-stable processes", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 14:52:42", "changeDate" : "2023-12-14 14:52:42", "count" : 2, "pub-type": "article", "journal": "Biometrika", "year": "2016", "url": "https://doi.org/10.1093/biomet/asw008", "author": [ "Clément Dombry","Sebastian Engelke","Marco Oesting" ], "authors": [ {"first" : "Clément", "last" : "Dombry"}, {"first" : "Sebastian", "last" : "Engelke"}, {"first" : "Marco", "last" : "Oesting"} ], "volume": "103","number": "2","pages": "303-317","abstract": "Max-stable processes play an important role as models for spatial extreme events. Their complex structure as the pointwise maximum over an infinite number of random functions makes their simulation difficult. Algorithms based on finite approximations are often inexact and computationally inefficient. We present a new algorithm for exact simulation of a max-stable process at a finite number of locations. It relies on the idea of simulating only the extremal functions, that is, those functions in the construction of a max-stable process that effectively contribute to the pointwise maximum. We further generalize the algorithm by Dieker \\& Mikosch (2015) for Brown\u2013Resnick processes and use it for exact simulation via the spectral measure. We study the complexity of both algorithms, prove that our new approach via extremal functions is always more efficient, and provide closed-form expressions for their implementation that cover most popular models for max-stable processes and multivariate extreme value distributions. For simulation on dense grids, an adaptive design of the extremal function algorithm is proposed.", "eprint" : "https://academic.oup.com/biomet/article-pdf/103/2/303/17460729/asw008.pdf", "issn" : "0006-3444", "doi" : "10.1093/biomet/asw008", "bibtexKey": "10.1093/biomet/asw008" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2d4cb70820a2f91a590584a7f419a0ce6/marcooesting", "tags" : [ "myown","peerreviewed" ], "intraHash" : "d4cb70820a2f91a590584a7f419a0ce6", "interHash" : "0a08fbb35b9eef7e7f6dd7b9fc60dbff", "label" : "L^p-norm spherical copulas", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 14:42:14", "changeDate" : "2023-12-14 14:42:14", "count" : 1, "pub-type": "article", "journal": "Journal of Multivariate Analysis","publisher":"Elsevier BV", "year": "2023", "url": "http://dx.doi.org/10.1016/j.jmva.2023.105262", "author": [ "Carole Bernard","Alfred Müller","Marco Oesting" ], "authors": [ {"first" : "Carole", "last" : "Bernard"}, {"first" : "Alfred", "last" : "Müller"}, {"first" : "Marco", "last" : "Oesting"} ], "pages": "105262", "issn" : "0047-259X", "doi" : "10.1016/j.jmva.2023.105262", "bibtexKey": "Bernard_2023" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/26c7f2fd7f7a9ae384bae4ffbdfe959d3/marcooesting", "tags" : [ "climxtreme","myown","ourc","ourwork","peerreviewed" ], "intraHash" : "6c7f2fd7f7a9ae384bae4ffbdfe959d3", "interHash" : "4a45af9df84674949fde4de3f7e59fd3", "label" : "Multivariate motion patterns and applications to rainfall radar data", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 12:11:07", "changeDate" : "2023-12-14 12:11:07", "count" : 2, "pub-type": "article", "journal": "Stochastic Environmental Research and Risk Assessment", "year": "2023", "url": "https://doi.org/10.1007/s00477-023-02626-7", "author": [ "Svenja Fischer","Marco Oesting","Alexander Schnurr" ], "authors": [ {"first" : "Svenja", "last" : "Fischer"}, {"first" : "Marco", "last" : "Oesting"}, {"first" : "Alexander", "last" : "Schnurr"} ], "abstract": "The classification of movement in space is one of the key tasks in environmental science. Various geospatial data such as rainfall or other weather data, data on animal movement or landslide data require a quantitative analysis of the probable movement in space to obtain information on potential risks, ecological developments or changes in future. Usually, machine-learning tools are applied for this task, as these approaches are able to classify large amounts of data. Yet, machine-learning approaches also have some drawbacks, e.g. the often required large training sets and the fact that the algorithms are often hard to interpret. We propose a classification approach for spatial data based on ordinal patterns. Ordinal patterns have the advantage that they are easily applicable, even to small data sets, are robust in the presence of certain changes in the time series and deliver interpretative results. They therefore do not only offer an alternative to machine-learning in the case of small data sets but might also be used in pre-processing for a meaningful feature selection. In this work, we introduce the basic concept of multivariate ordinal patterns and the corresponding limit theorem. A simulation study based on bootstrap demonstrates the validity of the results. The approach is then applied to two real-life data sets, namely rainfall radar data and the movement of a leopard. Both applications emphasize the meaningfulness of the approach. Clearly, certain patterns related to the atmosphere and environment occur significantly often, indicating a strong dependence of the movement on the environment.", "issn" : "1436-3259", "doi" : "10.1007/s00477-023-02626-7", "bibtexKey": "Fischer2023" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2a5c89cf9ff501043eb2da002350eae8e/marcooesting", "tags" : [ "myown","ourwork","peerreviewed" ], "intraHash" : "a5c89cf9ff501043eb2da002350eae8e", "interHash" : "dfa8ebff177d1d4706a973dfa1cebf9b", "label" : "Long memory of max-stable time series as phase transition: asymptotic behaviour of tail dependence estimators", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 12:07:36", "changeDate" : "2023-12-14 12:07:36", "count" : 2, "pub-type": "article", "journal": "Electronic Journal of Statistics","publisher":"Institute of Mathematical Statistics and Bernoulli Society", "year": "2023", "url": "https://doi.org/10.1214/23-EJS2181", "author": [ "Marco Oesting","Albert Rapp" ], "authors": [ {"first" : "Marco", "last" : "Oesting"}, {"first" : "Albert", "last" : "Rapp"} ], "volume": "17","number": "2","pages": "3316 -- 3336","abstract": "In this paper, we consider a simple estimator for tail dependence coefficients of a max-stable time series and show its asymptotic normality under a mild condition. The novelty of our result is that this condition does not involve mixing properties that are common in the literature. More importantly, our condition is linked to the transition between long and short range dependence (LRD/SRD) for max-stable time series. This is based on a recently proposed notion of LRD in the sense of indicators of excursion sets which is meaningfully defined for infinite-variance time series. In particular, we show that asymptotic normality with standard rate of convergence and a function of the sum of tail coefficients as asymptotic variance holds if and only if the max-stable time series is SRD.", "doi" : "10.1214/23-EJS2181", "bibtexKey": "10.1214/23-EJS2181" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/275050ece586ca5a0b18134b10b45b172/marcooesting", "tags" : [ "exc2075","myown","ourwork","peerreviewed" ], "intraHash" : "75050ece586ca5a0b18134b10b45b172", "interHash" : "85fccb20f82c03d452d364307626d907", "label" : "Detection of long range dependence in the time domain for (in)finite-variance time series", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 12:03:20", "changeDate" : "2024-09-23 11:18:49", "count" : 10, "pub-type": "article", "journal": "Statistics","publisher":"Taylor & Francis", "year": "2023", "url": "http://dx.doi.org/10.1080/02331888.2023.2287749", "author": [ "Marco Oesting","Albert Rapp","Evgeny Spodarev" ], "authors": [ {"first" : "Marco", "last" : "Oesting"}, {"first" : "Albert", "last" : "Rapp"}, {"first" : "Evgeny", "last" : "Spodarev"} ], "volume": "57","number": "6","pages": "1352-1379", "issn" : "1029-4910", "doi" : "10.1080/02331888.2023.2287749", "bibtexKey": "Oesting_2023" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/27403c5cb23934cb023a093a112159e33/marcooesting", "tags" : [ "ourwork","peerreviewed" ], "intraHash" : "7403c5cb23934cb023a093a112159e33", "interHash" : "fe90285268ac4259ff314c0a96bc7c1e", "label" : "Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation", "user" : "marcooesting", "description" : "", "date" : "2023-12-14 11:58:31", "changeDate" : "2023-12-14 11:58:31", "count" : 10, "pub-type": "article", "journal": "Bioinformatics","publisher":"Oxford University Press", "year": "2022", "url": "", "author": [ "Vincent Wagner","Benjamin Castellaz","Marco Oesting","Nicole Radde" ], "authors": [ {"first" : "Vincent", "last" : "Wagner"}, {"first" : "Benjamin", "last" : "Castellaz"}, {"first" : "Marco", "last" : "Oesting"}, {"first" : "Nicole", "last" : "Radde"} ], "volume": "38","number": "18","pages": "4352-4359", "research-areas" : "Biochemistry & Molecular Biology; Biotechnology & Applied\r\n Microbiology; Computer Science; Mathematical & Computational Biology;\r\n Mathematics", "language" : "eng", "issn" : "1367-4803 and 1460-2059", "affiliation" : "Radde, N (Corresponding Author), Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany.\r\n Radde, N (Corresponding Author), Univ Stuttgart, Stuttgart Ctr Simulat Sci, D-70569 Stuttgart, Germany.\r\n Wagner, Vincent; Castellaz, Benjamin; Radde, Nicole, Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany.\r\n Oesting, Marco; Radde, Nicole, Univ Stuttgart, Stuttgart Ctr Simulat Sci, D-70569 Stuttgart, Germany.\r\n Oesting, Marco, Univ Stuttgart, Inst Stochast & Applicat, D-70569 Stuttgart, Germany.", "orcid-numbers" : "Radde, Nicole/0000-0002-5145-0058", "unique-id" : "WOS:000835769300001", "doi" : "10.1093/bioinformatics/btac501", "bibtexKey": "wagner2022quasientropy" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/240629146dafc87566c3fc108b70f7fa6/marcooesting", "tags" : [ "myown","peerreviewed" ], "intraHash" : "40629146dafc87566c3fc108b70f7fa6", "interHash" : "db060b2aa64792ab0326cb6fa856975b", "label" : "Long range dependence for stable random processes", "user" : "marcooesting", "description" : "", "date" : "2023-02-28 18:37:26", "changeDate" : "2023-02-28 18:37:26", "count" : 3, "pub-type": "article", "journal": "J. Time Series Anal.", "year": "2021", "url": "https://doi.org/10.1111/jtsa.12560", "author": [ "Vitalii Makogin","Marco Oesting","Albert Rapp","Evgeny Spodarev" ], "authors": [ {"first" : "Vitalii", "last" : "Makogin"}, {"first" : "Marco", "last" : "Oesting"}, {"first" : "Albert", "last" : "Rapp"}, {"first" : "Evgeny", "last" : "Spodarev"} ], "volume": "42","number": "2","pages": "161--185", "mrclass" : "60G10 (60G52 60G70)", "fjournal" : "Journal of Time Series Analysis", "mrnumber" : "4303043", "issn" : "0143-9782", "doi" : "10.1111/jtsa.12560", "bibtexKey": "MR4303043" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2a46f8ed675f8b8aa066da9fee55b9aa8/marcooesting", "tags" : [ "myown","peerreviewed" ], "intraHash" : "a46f8ed675f8b8aa066da9fee55b9aa8", "interHash" : "628e2966307c66e63029293d14b4cbc0", "label" : "Ordinal patterns in clusters of subsequent extremes of regularly varying time series", "user" : "marcooesting", "description" : "", "date" : "2023-02-28 18:36:43", "changeDate" : "2023-02-28 18:36:43", "count" : 4, "pub-type": "article", "journal": "Extremes","publisher":"Springer", "year": "2020", "url": "", "author": [ "Marco Oesting","Alexander Schnurr" ], "authors": [ {"first" : "Marco", "last" : "Oesting"}, {"first" : "Alexander", "last" : "Schnurr"} ], "volume": "23","number": "4","pages": "521\u2013545", "research-areas" : "Mathematics", "language" : "eng", "issn" : "1386-1999 and 1572-915X", "affiliation" : "Oesting, M (Corresponding Author), Univ Siegen, Dept Math, Walter Flex Str 3, D-57068 Siegen, Germany.\r\n Oesting, M (Corresponding Author), Univ Stuttgart, Stuttgart Ctr Simulat Sci SC SimTech, Allmandring 5b, D-70569 Stuttgart, Germany.\r\n Oesting, M (Corresponding Author), Univ Stuttgart, Inst Stochast & Applicat, Allmandring 5b, D-70569 Stuttgart, Germany.\r\n Oesting, Marco; Schnurr, Alexander, Univ Siegen, Dept Math, Walter Flex Str 3, D-57068 Siegen, Germany.\r\n Oesting, Marco, Univ Stuttgart, Stuttgart Ctr Simulat Sci SC SimTech, Allmandring 5b, D-70569 Stuttgart, Germany.\r\n Oesting, Marco, Univ Stuttgart, Inst Stochast & Applicat, Allmandring 5b, D-70569 Stuttgart, Germany.", "unique-id" : "ISI:000562004800001", "doi" : "10.1007/s10687-020-00391-2", "bibtexKey": "oesting2020ordinal" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2a74504d01921c24b2bdf7921bd41f8cf/marcooesting", "tags" : [ "climxtreme","myown","preprint" ], "intraHash" : "a74504d01921c24b2bdf7921bd41f8cf", "interHash" : "0b04e39ea8d85c38fa85570e692e605f", "label" : "Patterns in Spatio-Temporal Extremes", "user" : "marcooesting", "description" : "", "date" : "2023-02-28 18:27:44", "changeDate" : "2023-02-28 18:29:49", "count" : 1, "pub-type": "preprint", "year": "2022", "url": "", "author": [ "Marco Oesting","Raphaël Huser" ], "authors": [ {"first" : "Marco", "last" : "Oesting"}, {"first" : "Raphaël", "last" : "Huser"} ], "note": "arXiv preprint arXiv:2212.11001", "preprinturl" : "https://arxiv.org/abs/2212.11001", "bibtexKey": "oesting2022patterns" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2770ee981f94af5755bc08a13762ecc08/marcooesting", "tags" : [ "exc2075","myown","ourwork","peerreviewed","pn5","pn5-10","updated" ], "intraHash" : "770ee981f94af5755bc08a13762ecc08", "interHash" : "aedacbc37c42ddd255f3febe5f2c247e", "label" : "A Comparative Tour through the Simulation Algorithms for Max-Stable Processes", "user" : "marcooesting", "description" : "", "date" : "2023-02-28 18:15:56", "changeDate" : "2024-12-30 16:45:22", "count" : 5, "pub-type": "article", "journal": "Statistical Science","publisher":"Institute of Mathematical Statistics", "year": "2022", "url": "", "author": [ "Marco Oesting","Kirstin Strokorb" ], "authors": [ {"first" : "Marco", "last" : "Oesting"}, {"first" : "Kirstin", "last" : "Strokorb"} ], "volume": "37","number": "1","pages": "42-63", "research-areas" : "Mathematics", "language" : "eng", "issn" : "0883-4237 and 2168-8745", "affiliation" : "Oesting, M (Corresponding Author), Univ Stuttgart, Stuttgart Ctr Simulat Sci, Computat Stat, D-70569 Stuttgart, Germany.\r\n Oesting, M (Corresponding Author), Univ Stuttgart, Inst Stochast & Applicat, D-70569 Stuttgart, Germany.\r\n Oesting, Marco, Univ Stuttgart, Stuttgart Ctr Simulat Sci, Computat Stat, D-70569 Stuttgart, Germany.\r\n Oesting, Marco, Univ Stuttgart, Inst Stochast & Applicat, D-70569 Stuttgart, Germany.\r\n Strokorb, Kirstin, Cardiff Univ, Sch Math, Cardiff CF24 4AG, Wales.", "unique-id" : "WOS:000745960400003", "doi" : "10.1214/20-STS820", "bibtexKey": "oesting2022comparative" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/22779669890e14d8f53d6b2b8c03ff9da/marcooesting", "tags" : [ "exc2075","myown","ourwork","ownwork","pn2","pn5" ], "intraHash" : "2779669890e14d8f53d6b2b8c03ff9da", "interHash" : "fe90285268ac4259ff314c0a96bc7c1e", "label" : "Quasi-Entropy Closure : a fast and reliable approach to close the moment equations of the Chemical Master Equation", "user" : "marcooesting", "description" : "", "date" : "2023-02-28 18:08:47", "changeDate" : "2023-02-28 18:08:47", "count" : 10, "pub-type": "article", "journal": "Bioinformatics","publisher":"Oxford University Press", "year": "2022", "url": "", "author": [ "Vincent Wagner","Benjamin Castellaz","Marco Oesting","Nicole Radde" ], "authors": [ {"first" : "Vincent", "last" : "Wagner"}, {"first" : "Benjamin", "last" : "Castellaz"}, {"first" : "Marco", "last" : "Oesting"}, {"first" : "Nicole", "last" : "Radde"} ], "volume": "38","number": "18","pages": "4352-4359", "research-areas" : "Biochemistry & Molecular Biology; Biotechnology & Applied\r\n Microbiology; Computer Science; Mathematical & Computational Biology;\r\n Mathematics", "language" : "eng", "issn" : "1367-4803 and 1460-2059", "affiliation" : "Radde, N (Corresponding Author), Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany.\r\n Radde, N (Corresponding Author), Univ Stuttgart, Stuttgart Ctr Simulat Sci, D-70569 Stuttgart, Germany.\r\n Wagner, Vincent; Castellaz, Benjamin; Radde, Nicole, Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany.\r\n Oesting, Marco; Radde, Nicole, Univ Stuttgart, Stuttgart Ctr Simulat Sci, D-70569 Stuttgart, Germany.\r\n Oesting, Marco, Univ Stuttgart, Inst Stochast & Applicat, D-70569 Stuttgart, Germany.", "orcid-numbers" : "Radde, Nicole/0000-0002-5145-0058", "unique-id" : "WOS:000835769300001", "doi" : "10.1093/bioinformatics/btac501", "bibtexKey": "wagner2022quasientropy" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2a0709b285049e3d0efe44e72d3720de7/marcooesting", "tags" : [ "climxtreme","myown","peerreviewed" ], "intraHash" : "a0709b285049e3d0efe44e72d3720de7", "interHash" : "b1d82a69885d66d80763627cceb7955f", "label" : "Implications of modeling seasonal differences in the extremal dependence of rainfall maxima", "user" : "marcooesting", "description" : "", "date" : "2023-02-28 17:55:15", "changeDate" : "2023-02-28 18:28:44", "count" : 1, "pub-type": "article", "journal": "Stochastic Environmental Research and Risk Assessment", "year": "2022", "url": "https://doi.org/10.1007/s00477-022-02375-z", "author": [ "Oscar E. Jurado","Marco Oesting","Henning W. Rust" ], "authors": [ {"first" : "Oscar E.", "last" : "Jurado"}, {"first" : "Marco", "last" : "Oesting"}, {"first" : "Henning W.", "last" : "Rust"} ], "abstract": "For modeling extreme rainfall, the widely used Brown\u2013Resnick max-stable model extends the concept of the variogram to suit block maxima, allowing the explicit modeling of the extremal dependence shown by the spatial data. This extremal dependence stems from the geometrical characteristics of the observed rainfall, which is associated with different meteorological processes and is usually considered to be constant when designing the model for a study. However, depending on the region, this dependence can change throughout the year, as the prevailing meteorological conditions that drive the rainfall generation process change with the season. Therefore, this study analyzes the impact of the seasonal change in extremal dependence for the modeling of annual block maxima in the Berlin-Brandenburg region. For this study, two seasons were considered as proxies for different dominant meteorological conditions: summer for convective rainfall and winter for frontal/stratiform rainfall. Using maxima from both seasons, we compared the skill of a linear model with spatial covariates (that assumed spatial independence) with the skill of a Brown\u2013Resnick max-stable model. This comparison showed a considerable difference between seasons, with the isotropic Brown\u2013Resnick model showing considerable loss of skill for the winter maxima. We conclude that the assumptions commonly made when using the Brown\u2013Resnick model are appropriate for modeling summer (i.e., convective) events, but further work should be done for modeling other types of precipitation regimes.", "issn" : "14363259", "refid" : "Jurado2022", "doi" : "10.1007/s00477-022-02375-z", "bibtexKey": "jurado2022implications" } ] }