GRK 1644:  Scaling Problems in Statistics

• Subject Area: Agriculture, Forestry and Veterinary Medicine ; Mathematics
• Term: from 2010 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 152112243

• Final Report Year: 2020

Final Report Abstract

This research training group (RTG) focused on “Scaling Problems in Statistics” as a general framework for developing, extending and applying statistical methodology related to scaling problems. In a broad sense, the notion of scale and associated scaling problems can be understood as an encompassing concept for challenges in empirical analysis where the units of observation behave differently when studying them on different scales. This implies that the measurement scale, and in particular the central properties of resolution and extent, have to be taken into account in statistical analyses. Thereby scales can represent very different concepts, ranging from spatial and temporal scales as the most obvious examples, over different levels of aggregation (e.g. from individuals over households to communities or states), to different levels of genetic information (e.g. in a functional scale from single base pairs over genes to pathways of genes). In this RTG, we have been treating scaling as a particular type of contextual information that has to be taken into account appropriately to provide meaningful results for research questions, such as “How does the association of animal and plant abundance depend on ecological conditions?”, “What impact has the price of one product on that of another?” or “How does genetic variation impact susceptibility towards a specific disease or the prediction of a genetically affected trait?” In all these cases, the result crucially depends on the scale chosen for the statistical analysis. Statistical methodology formed the core of the RTG, providing the interface between the considered areas of application (ecology, economics, genetics). This setup allowed us to stimulate methodological innovations based on challenging applications, to transfer general methodological innovations to the applied areas, and to foster the transfer of methods between the different areas of application. The methodological framework for the RTG was formed by mixed models, spatial statistics and distributional regression, roughly corresponding to the notions of hierarchical scales (mixed models), spatial scales (spatial statistics), and the measurement scale (distributional regression), respectively. For some specific projects, additional methodological topics such as networks or kernel regression were considered in addition. The interdisciplinarity of the research agenda of the RTG was also well reflected in the qualification program. The first core element, introductions to mixed models and spatial statistics, provided the PhD students with advanced knowledge in statistical methods dealing with scaling problems. Building on this common ground, further subjects were introduced in the form of specialization courses, research colloquia, and research seminars. A further important ingredient in qualification were courses on key competencies, including mandatory courses on “Diversity Competence”, “Good Scientific Practice” and “Collecting and Archiving Research Data”. Based on the experience from two successful funding phases and three cohorts of PhD students, we have convincing evidence for the stimulating environment that an interdisciplinary group with a methods-driven research and qualification agenda provides for young scientists. The PhD alumni of the RTG report very positively about the experiences they gained from their work in the RTG and in particular highlight the relevance of interdisciplinary collaboration and communication for their future careers in academia as well as in companies. We were able to develop important and innovative research results, where the interdisciplinary setup was stimulating the development of methods via exposure to challenging applied research problems on the one hand and the transfer of novel methods to applications on the other hand.

Publications

• (2011), Coverage of exon-targeted sequencing, in: C. Hemmelmann, P. Ahnert, R. Foraita, A. Groÿhennig, A. Scherag & K.E. Biebler (Eds.), Biometrische Aspekte der Genomanalyse 4. Next generation sequencing data analysis, 91-97, Shaker, ISBN 9783844001556
  Freytag, S., Sohns, M. & Bickeböller, H.
  
• (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
  Freytag, S., Bickeböller, H., Amos, C.I., Kneib, T. & Schlather, M.
  (See online at https://doi.org/10.1159/000347188)
• (2012), Effects of habitat isolation and predation pressure on an arboreal food-web, Community Ecology 13: 82-87
  Herrmann, J., Kormann, U., Schüepp, C., Stocker, Y., Herzog, F. & Entling, M.
  (See online at https://doi.org/10.1556/comec.13.2012.1.10)
• (2012), Forest monitoring for REDD+: challenges in mapping forest carbon, in: L. Fehrman & C. Kleinn (Eds.), Forest in Climate Change Research and Policy: The Role of Forest Management and Conservation in a Complex International Setting. Proceedings of the 2nd International DAAD Workshop December 2011, Pietermaritzburg and Durban, South Africa, 129-136, Cullivier Verlag, Göttingen
  Mundhenk, P.
  
• (2012), Instant trend-seasonal decomposition of time series with splines, Courant Research Centre Poverty, Equity and Growth - Discussion Papers 131: 1-26
  Rosales, F. & Krivobokova, T.
  
• (2012), Intrinsically weighted means of marked point processes
  Malinowski, A., Schlather, M. & Zhang, Z.
  (See online at https://doi.org/10.48550/arXiv.1210.1335)
• (2012), Parsimony-based pedigree analysis and individual-based landscape genetics suggest topography to restrict dispersal and connectivity in the endangered capercaillie, Biological Conservation 152: 241-252
  Kormann, U., Gugerli, F., Ray, N., Excoffier, L. & Bollmann, K.
  (See online at https://doi.org/10.1016/j.biocon.2012.04.011)
• (2013), A network-based kernel machine test for the identification of risk pathways in genome-wide association studies, Human Heredity 76: 64-75
  Freytag, S., Manitz, J., Schlather, M., Kneib, T., [...] & Bickeböller, H.
  (See online at https://doi.org/10.1159/000357567)
• (2013), Bayesian outbreak detection algorithm for monitoring reported cases of campylobacteriosis in Germany, Biometrical Journal 55: 509-526
  Manitz, J. & Höhle, M.
  (See online at https://doi.org/10.1002/bimj.201200141)
• (2013), Comparison of three summary statistics for ranking genes in genome-wide association studies, Statistics in Medicine
  Freytag, S. & Bickeböller, H.
  (See online at https://doi.org/10.1002/sim.6063)
• (2013), Enhanced structural complexity index: An improved index for describing forest structural complexity, Open Journal of Forestry 3: 23-29
  Beckschäfer, P., Mundhenk, P., Kleinn, C., Ji, Y., Yu, D.W. & Harrison, R.D.
  (See online at https://dx.doi.org/10.4236/ojf.2013.31005)
• (2013), Estimating predition error in mixed models, in: V.M.R.Muggeo, V. Capursi, G. Boscaino & G. Lovison (Eds.), Proceedings of the 28th International Workshop on Statistical Modelling, vol. 1, 363-368
  Säfken, B., Greven, S. & Kneib, T.
  
• (2013), Financial models of interaction based on marked point processes and Gaussian fields, Ph.D. thesis, Georg-August-Universität Göttingen
  Malinowski, A.
  (See online at https://dx.doi.org/10.53846/goediss-3364)
• (2013), Friends or foes? Interplay of facilitation and competition depends on the interaction between abiotic stress and ontogenetic stage, Plant Ecology 214: 1485-1492
  Beduschi, T. & Castellani, T.T.
  (See online at https://doi.org/10.1007/s11258-013-0269-8)
• (2013), The expected linkage disequilibrium infinite populations revisited
  Ober, U., Malinowski, A., Schlather, M. & Simianer, H.
  (See online at https://doi.org/10.48550/arXiv.1304.4856)
• (2014), A unifying approach to the estimation of the conditional akaike information in generalized linear mixed models, Electronic Journal of Statistics 8: 201-225
  Säfken, B., Kneib, T., van Waveren, C.S. & Greven, S.
  (See online at https://doi.org/10.1214/14-ejs881)
• (2014), BIOFRAG - a new database for analyzing BIOdiversity responses to forest FRAGmentation, Ecology and Evolution 4: 1524-1537
  Pfeifer, M., [...], Kormann, U., Scherber, C., Tscharntke, T., Tyre, A.J., Urbina Cardona, J.N.,Vasconcelos, H.L. et al.
  (See online at https://doi.org/10.1002/ece3.1036)
• (2014), Coverage and efficiency in current SNP chips, European Journal of Human Genetics 22: 1124-1130
  Ha, N.T., Freytag, S. & Bickeböller, H.
  (See online at https://doi.org/10.1038/ejhg.2013.304)
• (2014), Kernel methods for genes and networks to study genome-wide associations of lung cancer and rheumatoid arthritis, Ph.D. thesis, Georg-August-Universität Göttingen
  Freytag, S.
  (See online at https://dx.doi.org/10.53846/goediss-4373)
• (2014), Kernel score statistic for dependent data, BMC Proceedings 8: S41
  Malzahn, D., Friedrichs, S., Rosenberger, A. & Bickeböller, H.
  (See online at https://doi.org/10.1186/1753-6561-8-s1-s41)
• (2014), Statistical inference for max-stable processes by conditioning on extreme events, Advances in Applied Probability 46: 478-495
  Engelke, S., Malinowski, A., Oesting, M. & Schlather, M.
  (See online at https://doi.org/10.1239/aap/1401369703)
• (2014), Statistical inference for propagation processes on complex networks, Ph.D. thesis, Georg-August-Universität Göttingen
  Manitz, J.
  
• (2015), A scale-corrected comparison of linkage disequilibrium levels between genic and non-genic regions, PLOS ONE 10: e0141216+
  Berger, S., Schlather, M., de los Campos, G., Weigend, S., Preisinger, R., Erbe, M. & Simianer, H.
  (See online at https://doi.org/10.1371/journal.pone.0141216)
• (2015), Effectiveness of shrinkage and variable selection methods for the prediction of complex human traits using data from distantly related individuals, Annals of Human Genetics 79: 122-135
  Berger, S. & Pérez-Rodrlos Campos, G.
  (See online at https://doi.org/10.1111/ahg.12099)
• (2015), Estimation of Hüsler-Reiss distributions and Brown-Resnick processes, Journal of the Royal Statistical Society: Series B (Statistical Methodology) 77: 239-265
  Engelke, S., Malinowski, A., Kabluchko, Z. & Schlather, M.
  (See online at https://doi.org/10.1111/rssb.12074)
• (2015), Harnessing the biodiversity value of Central and Eastern European farmland, Diversity and Distributions 21: 722-730
  Sutcliffe, L.M.E., Batáry, P., Kormann, U., [...] & Tscharntke, T.
  (See online at https://doi.org/10.1111/ddi.12288)
• (2015), Hedgerows have a barrier effect and channel pollinator movement in the agricultural landscape, Journal of Landscape Ecology 8
  Klaus, F., Bass, J., Marholt, L., Müller, B., Klatt, B. & Kormann, U.
  (See online at https://doi.org/10.1515/jlecol-2015-0001)
• (2015), Integrating remotely sensed data into forest resource inventories, Ph.D. thesis, Georg-August-Universität Göttingen
  Mundhenk, P.
  
• (2015), Local and landscape management drive trait-mediated biodiversity of nine taxa on small grassland fragments, Diversity and Distributions 21: 1204-1217
  Kormann, U., Rösch, V., Batáry, P., Tscharntke, T., Orci, K.M., Samu, F. & Scherber, C.
  (See online at https://doi.org/10.1111/ddi.12324)
• (2015), Model choice and variable selection in mixed & semiparametric models, Ph.D.thesis, Georg-August-Universität Göttingen
  Säfken, B.
  (See online at https://dx.doi.org/10.53846/goediss-5020)
• (2015), Modeling microbial growth and dynamics, Applied Microbiology and Technology 99
  Esser, D.S., Leveau, J.H.J. & Meyer, K.M.
  (See online at https://doi.org/10.1007/s00253-015-6877-6)
• (2015), Regional heterogeneity, geography and agglomeration effects in efficiency analysis: The case of dairy farming in Europe, Ph.D. thesis, Georg-August-Universität Göttingen
  Castro Medina, D.M.
  (See online at https://dx.doi.org/10.53846/goediss-4965)
• (2015), Scale dependence of pollinator community turnover and tritrophic interactions in changing landscapes, Ph.D. thesis, Georg-August-Universität Göttingen
  Beduschi, T.
  (See online at https://dx.doi.org/10.53846/goediss-4889)
• (2015), Scale effects on genomic modelling and prediction, Ph.D. thesis, Georg-August-Universität Göttingen
  Berger, S.
  (See online at https://dx.doi.org/10.53846/goediss-5230)
• (2015), Scale-dependent management of biodiversity and ecosystem processes in fragmented landscapes, Ph.D. thesis, Georg-August-Universität Göttingen
  Kormann, U.
  (See online at https://dx.doi.org/10.53846/goediss-5288)
• (2015), Sixty-seven years of land-use change in Southern Costa Rica, PLOS ONE 10: e0143554+
  Zahawi, R.A., Duran, G. & Kormann, U.
  (See online at https://doi.org/10.1371/journal.pone.0143554)
• (2015), Spatial scales of interactions among bacteria and between bacteria and the leaf surface, FEMS Microbiology Ecology 91
  Esser, D.S., Leveau, J.H.J., Meyer, K.M. & Wiegand, K.
  (See online at https://doi.org/10.1093/femsec/fiu034)
• (2015), Stochastic models in population genetics: The impact of selection and recombination, Ph.D. thesis, Georg-August-Universität Göttingen
  Brink-Spalink, R.
  (See online at https://dx.doi.org/10.53846/goediss-4998)
• (2015), The influence of scale on the measurement of the vertical price transmission, Ph.D. thesis, Georg-August-Universität Göttingen
  Tifaoui, S.
  (See online at https://dx.doi.org/10.53846/goediss-5864)
• (2015), Using multi-level generalized path analysis to understand herbivore and parasitoid dynamics in changing landscapes, Landscape Ecology 30:1975-1986
  Beduschi, T., Tscharntke, T. & Scherber, C.
  (See online at https://doi.org/10.1007/s10980-015-0224-2)
• (2016), A robust statistical approach to select adequate error distributions for financial returns, Journal of Applied Statistics 44: 137-161
  Hambuckers, J. & Heuchenne, C.
  (See online at https://doi.org/10.1080/02664763.2016.1165803)
• (2016), Behavioral studies on the use of open water basins by American mink (neovison vison), Journal of Veterinary Behavior: Clinical Applications and Research 13: 19-26
  Schwarzer, A., Bergmann, S., Manitz, J., Küchenhoff, H., Erhard, M. & Rauch, E.
  (See online at https://doi.org/10.1016/j.jveb.2016.02.007)
• (2016), Corridors restore animal-mediated pollination in fragmented tropical forest landscapes, Proceedings of the Royal Society B 283: 20152347
  Kormann, U., Scherber, C., Tscharntke, T., Klein, N., Larbig, M., Valente, J.J., Hadley, A.S. & Betts, M.G.
  (See online at https://doi.org/10.1098/rspb.2015.2347)
• (2016), Empirical Bayesian smoothing splines for signals with correlated errors: Methods and applications, Ph.D. thesis, Georg-August-Universität Göttingen
  Rosales, F.
  (See online at https://dx.doi.org/10.53846/goediss-5798)
• (2016), Epidemiological and ecological characterization of the EHEC O104:H4 outbreak in Hamburg, Germany, 2011, PLOS ONE 11: e0164508+
  Tahden, M., Manitz, J., Baumgardt, K., Fell, G., Kneib, T. & Hegasy, G.
  (See online at https://doi.org/10.1371/journal.pone.0164508)
• (2016), Estimating the out-of-sample predictive ability of trading rules: A robust bootstrap approach, Journal of Forecasting 35: 347-372
  Hambuckers, J. & Heuchenne, C.
  (See online at https://doi.org/10.1002/for.2380)
• (2016), NetOrigin: Origin estimation for propagation processes on complex networks
  Manitz, J. & Harbering, J.
  
• (2016), Smoothing parameter and model selection for general smooth models, Journal of the American Statistical Association 111: 1548-1563
  Wood, S.N., Pya, N. & Säfken, B.
  (See online at https://doi.org/10.1080/01621459.2016.1180986)
• (2016), Spillover of arthropods from cropland to protected calcareous grassland - the neighbouring habitat matters, Agriculture, Ecosystems & Environment 235: 127-133
  Madeira, F., Tscharntke, T., Elek, Z., Kormann, U., Pons, X., Rösch, V., Samu, F., Scherber, C. et al.
  (See online at https://doi.org/10.1016/j.agee.2016.10.012)
• (2017), Effect separation in regression models with multiple scales, Ph.D. thesis, Georg-August-Universität Göttingen
  Thaden, H.
  (See online at https://dx.doi.org/10.53846/goediss-6341)
• (2017), Genealogies of two linked neutral loci after a selective sweep in a large population of stochastically varying size, Advances in Applied Probability 49: 279-326
  Brink-Spalink, R. & Smadi, C.
  (See online at https://doi.org/10.1017/apr.2016.88)
• (2017), How can seed removal rates of zoochoric tree species be assessed quickly and accurately?, Forest Ecology and Management 403: 152-160
  Hambuckers, J., Dauvrin, A., Trolliet, F., Evrard, Q., Forget, P.M. & Hambuckers, A.
  (See online at https://doi.org/10.1016/j.foreco.2017.07.042)
• (2017), Integrating multivariate conditionally autoregressive spatial priors into recursive bivariate models for analyzing environmental sensitivity of mussels, Spatial Statistics 22: 419-433
  Thaden, H., Pata, M.P., Klein, N., Cadarso-Suárez, C. & Kneib, T.
  (See online at https://doi.org/10.1016/j.spasta.2017.07.005)
• (2017), kangar00: Kernel approaches for nonlinear genetic association regression
  Manitz, J., Friedrichs, S., Burger, P., Hofner, B., Ha, N.T., Freytag, S. & Bickeböller, H.
  
• (2017), Kernel-based pathway approaches for testing and selection, Ph.D. thesis, Georg-August-Universität Göttingen
  Friedrichs, S.
  (See online at https://dx.doi.org/10.53846/goediss-6520)
• (2017), Pathway-based kernel boosting for the analysis of genome-wide association studies, Computational and Mathematical Methods in Medicine 2017: 1-17
  Friedrichs, S., Manitz, J., [...], Kneib, T., Bickeböller, H. & Hofner, B.
  (See online at https://doi.org/10.1155/2017/6742763)
• (2017), Scales of bacterial interactions on the leaf surface, Ph.D. thesis, Georg-August-Universität Göttingen
  Esser, D.S.
  (See online at https://dx.doi.org/10.53846/goediss-6076)
• (2017), Scaling of animal communities: From local and landscape to global processes, Ph.D. thesis, Georg-August-Universität Göttingen
  Udy, K.
  (See online at https://dx.doi.org/10.53846/goediss-6634)
• (2017), Source estimation for propagation processes on complex networks with an application to delays in public transportation systems, Journal of the Royal Statistical Society: Series C (Applied Statistics) 66: 521-536
  Manitz, J., Harbering, J., Schmidt, M., Kneib, T. & Schöbel, A.
  (See online at https://doi.org/10.1111/rssc.12176)
• (2017), Temporary sales prices and asymmetric price transmission, Agribusiness 33: 85-97
  Tifaoui, S. & von Cramon-Taubadel, S.
  (See online at https://doi.org/10.1002/agr.21465)
• (2017), The role of heterogeneity in spatial plant population dynamics, Ph.D. thesis, Georg-August-Universität Göttingen
  van Waveren, C.S.
  (See online at https://dx.doi.org/10.53846/goediss-6543)
• (2018), A Markov-switching generalized additive model for compound Poisson processes, with applications to operational loss models, Quantitative Finance 18: 1679-1698
  Hambuckers, J., Kneib, T., Langrock, R. & Silbersdorff, A.
  (See online at https://doi.org/10.1080/14697688.2017.1417625)
• (2018), Adaptive non-parametric estimation of mean and autocovariance in regression with dependent errors
  Serra, P., Krivobokova, T. & Rosales, F.
  (See online at https://doi.org/10.48550/arXiv.1812.06948)
• (2018), Dualities and genealogies in stochastic population models, Ph.D. thesis, Georg-August-Universität Göttingen
  Mach, T.
  (See online at https://dx.doi.org/10.53846/goediss-6734)
• (2018), Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR, International Journal of Applied Earth Observation and Geoinformation 65: 12-23
  Kukunda, C.B., Duque-Lazo, J., González-Ferreiro, E., Thaden, H. & Kleinn, C.
  (See online at https://doi.org/10.1016/j.jag.2017.09.016)
• (2018), Health care service provision in Europe and regional diversity: a stochastic metafrontier approach, Health Economics Review 8
  Schley, K.
  (See online at https://doi.org/10.1186/s13561-018-0195-5)
• (2018), Heterogeneity of long-run technical efficiency of german dairy farms: A Bayesian approach, Journal of Agricultural Economics 69: 58-75
  Skevas, I., Emvalomatis, G. & Brümmer, B.
  (See online at https://doi.org/10.1111/1477-9552.12231)
• (2018), Improving health care service provision by adapting to regional diversity: An efficiency analysis for the case of Germany, Health Policy 122: 293-300
  Herwartz, H. & Schley, K.
  (See online at https://doi.org/10.1016/j.healthpol.2018.01.004)
• (2018), Local and landscape effects on arthropod communities along an arable-urban gradient, Ph.D. thesis, Georg-August-Universität Göttingen
  Reininghaus, H.
  (See online at https://dx.doi.org/10.53846/goediss-6864)
• (2018), Productivity growth measurement and decomposition under a dynamic inefficiency specification: The case of German dairy farms, European Journal of Operational Research 271: 250-261
  Skevas, I., Emvalomatis, G. & Brümmer, B.
  (See online at https://doi.org/10.1016/j.ejor.2018.04.050)
• (2018), Relating drug response to epigenetic and genetic markers using a region-based kernel score test, BMC Proceedings 12: 47
  Yasmeen, S., Burger, P., Friedrichs, S., Papiol, S. & Bickeböller, H.
  (See online at https://doi.org/10.1186/s12919-018-0154-5)
• (2018), Schätzverfahren für individuelles Preissetzungsverhalten im Lebensmitteleinzelhandel, Ph.D. thesis, Georg-August-Universität Göttingen
  Schulze Bisping, C.
  (See online at https://dx.doi.org/10.53846/goediss-6675)
• (2018), Somewhere in between towns, markets, and neighbors: Agricultural transition in the rural-urban interface of Bangalore, India, courant Research Centre Poverty, Equity and Growth Discussion Papers 256: 1-20
  Steinhübel, L.
  (See online at https://doi.org/10.1080/00220388.2020.1806244)
• (2018), Spatial community turnover of pollinators is relaxed by semi-natural habitats, but not by mass-owering crops in agricultural landscapes, Biological Conservation 221: 59-66
  Beduschi, T., Kormann, U., Tscharntke, T. & Scherber, C.
  (See online at https://doi.org/10.1016/j.biocon.2018.01.016)
• (2018), Structural equation models for dealing with spatial confounding, The American Statistician 72: 239-252
  Thaden, H. & Kneib, T.
  (See online at https://doi.org/10.1080/00031305.2017.1305290)
• (2018), The effect of farm characteristics on the persistence of technical inefficiency: a case study in German dairy farming, European Review of Agricultural Economics 45: 3-25
  Skevas, I., Emvalomatis, G. & Brümmer, B.
  (See online at https://doi.org/10.1093/erae/jbx019)
• (2018), The provision of medical services, regional diversity, and population well-being: A health frontier approach, Ph.D. thesis, Georg-August-Universität Göttingen
  Schley, K.
  
• (2018), Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach, Journal of Applied Econometrics
  Hambuckers, J., Groll, A. & Kneib, T.
  (See online at https://doi.org/10.1002/jae.2638)
• (2018),Density-dependent spatial patterning of woody plants differs between a semi-arid and a mesic savanna in South Africa, Journal of Arid Environments 157: 103-112
  Hesselbarth, M.H.K., Wiegand, K., Dreber, N., Kellner, K., Esser, D.S. & Tsvuura, Z.
  (See online at https://doi.org/10.1016/j.jaridenv.2018.06.002)
• (2019), A unied framework for land cover monitoring based on a discrete global sampling grid (GSG), Environmental Monitoring and Assessment 191
  Fehrmann, L., Kukunda, C.B., Nölke, N., Schnell, S., Seidel, D., Magnussen, S. & Kleinn, C.
  (See online at https://doi.org/10.1007/s10661-018-7152-y)
• (2019), Analyzing the relationship between historic canopy dynamics and current plant species diversity in the herb layer oftemperate forests using long-term Landsat time series, Remote Sensing of Environment 232: 111305
  Graf, W., Kleinn, C., Schall, P., Nauss, T., Detsch, F. & Magdon, P.
  (See online at https://doi.org/10.1016/j.rse.2019.111305)
• (2019), Bayesian effect selection in structured additive distributional regression models
  Klein, N., Carlan, M., Kneib, T., Lang, S. & Wagner, H.
  
• (2019), Estimating value-at-risk for the g-and-h distribution: an indirect inference approach, Quantitative Finance 19: 1255-1266
  Bee, M., Hambuckers, J. & Trapin, L.
  (See online at https://doi.org/10.1080/14697688.2019.1580762)
• (2019), Land-sharing/-sparing connectivity landscapes for ecosystem services and biodiversity conservation, People and Nature 1: 262-272
  Grass, I., [...], Librán-Embid, F., Klaus, F., Udy, K. & Tscharntke, T.
  (See online at https://doi.org/10.1002/pan3.21)
• (2019), LASSO-type penalization in the framework of generalized additive models for location, scale and shape, Computational Statistics & Data Analysis 140: 59-73
  Groll, A., Hambuckers, J., Kneib, T. & Umlauf, N.
  (See online at https://doi.org/10.1016/j.csda.2019.06.005)
• (2019), Lost in translation: On the problem of data coding in penalized whole genome regression with interactions, G3:Genes|Genomes|Genetics
  Martini, J.W.R., Rosales, F., Ha, N.T., Heise, J., Wimmer, V. & Kneib, T.
  (See online at https://doi.org/10.1534/g3.118.200961)
• (2019), Multivariate effect priors in bivariate semiparametric recursive gaussian models, Computational Statistics & Data Analysis 137: 51-66
  Thaden, H., Klein, N. & Kneib, T.
  (See online at https://doi.org/10.1016/j.csda.2018.12.004)
• (2019), Polygenic risk for schizophrenia and global assessment of functioning - a comparison with in-silico data, Journal of Psychiatry and Brain Science
  Yasmeen, S., Papiol, S., Falkai, P., Schulze, T.G. & Bickeböller, H.
  (See online at https://doi.org/10.20900/jpbs.20190003)
• (2019), Provision of health care services and regional diversity in Germany: insights from a Bayesian health frontier analysis with spatial dependencies, The European Journal of Health Economics
  Haschka, R.E., Schley, K. & Herwartz, H.
  (See online at https://doi.org/10.1007/s10198-019-01111-9)
• (2019), Scale-guided mapping of forest stand structural heterogeneity from airborne LiDAR, Ecological Indicators 102: 410-425
  Kukunda, C.B., Beckschäfer, P., Magdon, P., Schall, P., Wirth, C. & Kleinn, C.
  (See online at https://doi.org/10.1016/j.ecolind.2019.02.056)
• (2019), Urbanization, agricultural intensification, and environmental services: A spatial analysis, Ph.D. thesis, Georg-August-Universität Göttingen
  Steinhübel, L.
  (See online at https://dx.doi.org/10.53846/goediss-7745)
• (2020), Noncrossing structured additive multiple-output bayesian quantile regression models, Statistics and Computing 97: 825
  Santos, B. & Kneib, T.
  (See online at https://doi.org/10.1007/s11222-020-09925-x)