Dr. Nadja Klein

• since 07/2016: Postdoctoral Feodor-Lynen-Fellow of the Alexander von Humboldt Foundation, Melbourne Business School, University of Melbourne
• 10/2015-07/2016: Postdoctoral Fellow of the Fonds Wetenschappelijk Onderzoek - Vlaanderen, Supervisor: Prof. Dr. Gerda Claeskens (unpaid leave)
• 2015: Postdoctoral researcher, Georg-August-Universität Göttingen
• 2012-2014: PhD project Bayesian Structured Additive Distributional Regression (within the DFG Research Project "Structured Additive Quantile and Expectile Regression" (03/2012 - 02/2014) and the DFG Research Project "Structured Additive Distributional Regression" (since 03/2014), supervised by Prof. Dr. Thomas Kneib). Defense (Dr. rer. nat. in Mathematics): 03/12/2014
• 2012-2014: Member of the RTG 1644 "Scaling Problems in Statistics"
• 2013-2014: Mentee within the "Dorothea Schlözer Mentoring Programme 2013 / 2014"

Prices and Awards:



• since 07/2016: Member of the Humboldt network (Alexander von Humboldt Foundation)
• 2015: Wolfgang-Wetzel-Price 2015 of the German Statistical Society for the paper Bayesian Generalized Additive Models for Location, Scale and Shape for Zero-Inflated and OverdispersedCount Data
• 2014: Award of the Georg-August-Universitaet Goettingen for outstanding dissertation Bayesian Structured Additive Distributional Regression
• 2014: Award of the Universitaetsbund Goettingen for the dissertation Bayesian Structured Additive Distributional Regression

Memberships:



• since 2018: Member of The German Statistical Society (DStatG)
• since 2018: American Statistical Association (ASA) Early Career Member
• since 2017: Member of The German Association of University Professors and Lecturers (DHV)
• since 2017: Member of the Bayesian Analysis and Modeling Research Group, University of Melbourne
• since 2015: Member of the Centre for Statistics, University of Goettingen
• 2012-2014: Member of the RTG 1644 "Scaling Problems in Statistics"

Research Interests:



• Bayesian Statistics
• Computational Methods
• Machine Learning
• Distributional Regression
• Smoothing Methods
• Copula Modelling
• Shrinkage Priors and Variable Selection

Research Stays:



• Research visit (within the DAAD project "Extended Structured Additive Regression and its Applications"), Department of Biostatistics, University of Santiago de Compostela, Spain (06/2014)
• Research visit, Department of Statistics, University of Innsbruck, Austria (04/2013)
• Research visit, Department of Statistics, University of Innsbruck, Austria (01/2013)

Peer-Reviewed Publications and Book Chapters:



1. Helbich, M., Klein, N., Roberts, H., Hagedoorn, P., Groenewegen, P. (2018)
   More green space is related to less antidepressant prescription rates in the Netherlands: A Bayesian geoadditive quantile regression approach.
   To appear in Environmental Research.
2. Ríos-Pena, L., Kneib, T., Cadarso-Suarez, C., Klein, N. and Marey-Pérez, M. (2018)
   Studying the Occurrence and Burnt Area of Wildfires using Zero-One-Inflated Structured Additive Beta Regression.
   To appear in Environmental Modelling and Software.
3. Umlauf, N., Klein, N. and Zeileis, A. (2018)
   BAMLSS: Bayesian Additive Models forLocation, Scale and Shape (and Beyond).
   To appear in Journal of Computational and Graphical Statistics.
4. Michaelis, P., Klein, N. and Kneib, T. (2017)
   Bayesian Multivariate Distributional Regression with Skewed Responses and Skewed Random Effects.
   To appear in Journal of Computational and Graphical Statistics.
5. Duarte, E., de Sousa, B., Cadarso Suárez, C., Klein, N., Kneib, T. and Rodrigues, V. (2017)
   Studying the relationship between a woman's reproductive life span and age at menarche using a Bayesian multivariate structured additive distributional regression model. To appear in Biometrical Journal.
6. Thaden, H., Pata, M. P., Klein, N., Cadarso Suarez, C. and Kneib, T. (2017)
   Integrating Multivariate Conditionally Autoregressive Spatial Priors into Recursive Bivariate Models for Analyzing Environmental Sensitivity of Mussels.
   To appear in Spatial Statistics.
7. Mamouridis, V., Klein, N., Kneib, T., Cadarso Suarez, C. and Maynou, F. (2016)
   Structured Additive Distributional Regression for Analyzing Landings per Unit Effort Indices in Fisheries Research.
   To appear in Mathematical Biosciences.
8. Waldmann, E., Taylor-Robinson D., Klein N., Kneib T., Pressler T., Schmid, M. and Mayr, A.(2017):
   Boosting Joint Models for Longitudinal and Time-to-Event Data.
   To appear in Biometrical Journal, 59, 1104--1121. .
9. Klein, N. and Kneib, T. (2016)
   Scale-Dependent Priors for Variance Parameters in Structured Additive Distributional Regression.
   Bayesian Analysis, 11, 1071-1106, doi:10.1214/15-BA983.
10. Kormann, U., Scherber, C., Tscharnke, T. Klein, N., Larbig, M, Valente, J., Hadley, A. and Betts, M. (2016)
    Corridors Restore Animal-Mediated Pollination in Fragmented Tropical Forest Landscapes.
    Proceedings of the Royal Society B, 283, doi:10.1098/rspb.2015.2347.
11. März, A., Klein, N., Kneib, T. and Mußhoff, O. (2016)
    Analysing farmland rental rates using Bayesian geoadditive quantile regression.
    European Review of Agricultural Economics, 43, 663-–698, doi:10.1093/erae/jbv028.
12. Klein, N. and Kneib, T. (2016)
    Simultaneous Inference in Structured Additive Conditional Copula Regression Models: A Unifying Bayesian Approach.
    Statistics and Computing, 26, 841--860, doi:10.1007/s11222-015-9573-6.
13. Klein, N., Kneib, T., Lang, S. and Sohn, A. (2015)
    Bayesian Structured Additive Distributional Regression with an Application to Regional Income Inequality in Germany.
    Annals of Applied Statistics, 9, 1024-1052.
14. Herwartz, H., Klein, N. and Strumann, C. (2016)
    Modelling hospital admission and length of stay by means of generalised count data models.
    Journal of Applied Econometrics, 6, 1159-1182, doi:10.1002/jae.2454.
15. Sohn, A., Klein, N. and Kneib, T. (2015)
    A Semiparametric Analysis of Conditional Income Distributions.
    Schmollers Jahrbuch - Journal of Applied Science Studies, 135, 13-22, doi:10.3790/schm.135.1.13.
16. Klein, N., Kneib, T., Klasen, S. and Lang, S. (2015)
    Bayesian Structured Additive Distributional Regression for Multivariate Responses.
    Journal of the Royal Statistical Society: Series C, 64, 569-591, doi:10.1111/rssc.12090.
17. Klein, N., Kneib, T. and Lang, S. (2015)
    Bayesian Generalized Additive Models for Location, Scale and Shape for Zero-Inflated and Overdispersed Count Data.
    Journal of the American Statistical Association, 110, 405-419, doi:10.1080/01621459.2014.912955.
18. Klein, N., Denuit, M., Lang, S. and Kneib, T. (2014)
    Nonlife ratemaking and risk management with Bayesian generalized additive models for location, scale, and shape.
    Insurance: Mathematics and Economics, 55, 225-249.
19. Razen, A., Brunauer, W., Klein, N., Lang, S. and Umlauf, N. (2014)
    Hedonic House Price Modeling based on Multilevel Structured Additive Regression,
    to appear in Computational Approaches for Urban Economics, Springer Verlag. Edited by Helbich, M., Jokar, J. und Leitner, M.

Other Publications:



1. Klein, N., Gude, F., Cadarso-Suárez, C. and Kneib, T. (2014)
   Bivariate Gaussian Distributional Regression: An Application on Diabetes,
   in 'Proceedings of the 29th International Workshop on Statistical Modelling', T. Kneib, F. Sobotka, J.Fahrenholz, H. Irmer, eds. Vol. 1, pp. 167-172.
2. Klein, N., Kneib, T. and Lang, S. (2013)
   Bayesian generalized additive models for location, scale
   and shape for insurance data,
   in 'Proceedings of the 29th International Workshop on Statistical Modelling', V. M. R. Muggeo, V. Capursi, G. Boscaino and G. Lovison, eds. Vol. 2, pp. 645-650.

Submitted Papers:


Mixed Discrete-Continuous Regression - A Novel Approach Based on Weight Functions.
1. Mascarenhas, A., Marques, F., Silva, S., Gouveia, S., Alves, M., Virella, D., Papoila, A. L., Kneib, T., Klein, N. and Neto, M. T. (2017)
   Determinants of the Variability of Oxygen Saturation during the First Minutes of Life of Term Neonates.
2. Klein, N., Malzahn, D., Rosenberger, A., Lozano-Kühne, J., Kneib, T. and Bickeböller, H. (2016)
   Candidate gene association analysis for a continuous phenotype with a spike at zero using parent-offspring trios.
3. Klein, N. and Kneib, T. (2016)
   New Notion of Bivariate Quantiles based on the Cumulative Distribution Function.
4. Oelker, M. R., Sobotka, F., Klein, N. and Kneib, T. (2014)
   Semiparametric Mode Regression.
5. Klein, N., Kneib, T. and Lang, S. (2013)
   Bayesian Structured Additive Distributional Regression.

Software:



1. BayesX - Bayesian Inference in Structured Additive Regression Models
2. Contributions to the R-package BayesX: R Utilities Accompanying the Software Package BayesX.
3. R-package BayesR.
4. R-package sdPrior.
5. R-package bivquant.

Editorial Work & Refereeing Service:



• Guest Editor of Biometrical Journal (Special Issue 'Joint Modelling of Longitudinal and Time-To-Event Data and Beyond').
• Referee for: Annals of Applied Statistics, Biometrical Journal, Journal of the American Statistical Association, Scandinavian Journal of Statistics, Statistics, Statistics and Computing.

Third Party Funding:



• 07/2016–06/2018 Feodor-Lynen fellowship of the Alexander von Humboldt Stiftung (principle investigator: N. Klein; 2016-2018)
• 10/2017–03/2022 RTG 2300 Enrichment of European beech forests with conifers: impacts of functional
  traits on ecosystem functioning (speaker: Christian Ammer; own role: principle investigator)

Presentations:



• Poster: The Implicit Copula of Bayesian Regularized Regression Smoothers at International Society for Bayesian Analysis World-Meeting (Edinburgh, 24/06/2018-29/06/2018)
• Talk: A Principled Prior for Variances in Distributional Regression at 9th Workshop on Spatio-Temporal Modelling (Montpellier, 13/06/2018-15/06/2018)
• Invited Talk at the Empirical Economics and Econometrics Seminar: A Novel Class of Semiparametric Distributional Models (University of Innsbruck, 21/05/2018-25/05/2018)
• Invited Talk (appointment for a tenured W2 professorship): The Implicit Copula of Bayesian Regularized Regression Smoothers (Munich, 12/04/2018-13/03/2018)
• Invited Talk: Scale-Dependent Priors for Variance Parameters in Hierarchichal Regression Models at the Research Colloquium, The University of Sydney Business School (Sydney, 24/08/2017-26/08/2017)
• Talk: Scale-Dependent Priors for Variance Parameters in Distributional Regression at 11th Annual RCEA Bayesian Econometric Workshop (Melbourne, 03/07/2017-05/07/2017)
• Invited Talk: Scale-Dependent Priors for Variance Parameters in Distributional Regression at the Research Colloquium, RTG 1644 (Goettingen, 09/2016)
• Poster: Scale-Dependent Priors for Variance Parameters in Distributional Regression at International Society for Bayesian Analysis Worldmeeting (Sardinia, 13/07/2016-17/06/2016)
• Invited Talk: On (Multivariate) Distributional Regression at the Statistics and Econometrics Research Seminar (University of Bielefeld, 22/01/2015)
• Poster: Scale-Dependent Priors for Variance Parameters in Distributional Regression at Autumn meeting on Latent Gaussian Models 2015 (Trondheim, 17/09/2015-18/09/2015)
• Talk: Scale-Dependent Priors for Variance Parameters in Distributional Regression at 30th International Workshop on Statistical Modelling (Linz, 06/07/2015-10/07/2015)
• Invited Talk: Bayesian Structured Additive Distributional Regression at the Statistics Seminar (KU Leuven, 20/06/2015)
• Invited Talk: Multivariate Distributional Regression at the Statistics Research Seminar (University of Linz, 22/01/2015)
• Talk: Simultaneous Inference in Structured Additive Conditional Copula Regression Models at 7th International Conference of the ERCIM Working Group on Computational and Methodological Statistics (Pisa, 06/12/2014-08/12/2014)
• Talk: Bivariate Extensions of Structured Additive Distributional Regression based on Conditional Copula Models at Österreichische Statistiktage (Innsbruck, 09/09/2014-12/09/2014)
• Talk: Bivariate Gaussian Distributional Regression: An Application on Diabetes at 29th International Workshop on Statistical Modelling (Göttingen, 14/07/2014-18/07/2014)
• Invited Talk: Bivariate Gaussian Distributional Regression: An Application on Diabetes at the Workshop: Young Researchers in Biostatistics (University of Santiago de Compostela, 11/06/2014)
• Invited Talk: Bayesian Structured Additive Distributional Regression at the Empirical Economics and Econometrics Seminar (University of Innsbruck, 04/12/2013)
• Invited Talk: An Introduction to Bayesian Structured Additive Distributional Regression at the Biostatistics Research Seminar (University of Santiago de Compostela, 29/10/2013)
• Poster: Bayesian Generalised Additive Models for Location, Scale, and Shape applied to Insurance Data at 28th International Workshop on Statistical Modelling (Palermo, 08/07/2013-12/07/2013)
• Talk: Multivariate Gaussian Distributional Regression at 19. DStatG Nachwuchsworkshop (Berlin, 16/09/2013-18/09/2013)
• Talk: Bayesian Generalised Additive Models for Location, Scale, and Shape for Zero-Inflated and Overdispersed Count Data at the 3rd joint Statistical Meeting DAGStat 2013 (Freiburg, 18/03/2013-21/03/2013)
• Talk: Bayesian Generalised Additive Models for Location, Scale, and Shape for Zero-Inflated Count Data at 5th International Conference of the ERCIM Working Group on Computational and Methodological Statistics (Oviedo 01/12/2012-03/12/2012)
• Talk: Spatial Smoothing in Zero-Inflated Count Data at the Research Seminar "Spatial Regression Models" (Göttingen, 12/02/2013)

Teaching:




Winter Term 2015/16



• Graduate Seminar in Applied Statistics
• Vorkurs Mathematische Grundlagen der Angewandten Statistik

Summer Term 2015

Winter Term 2014/15

Summer Term 2014

Winter Term 2013/14

Summer Term 2013

Winter Term 2012/13

Summer Term 2012

Supervision and Volunteering:



• Supervisor, PhD thesis of Isa Marques: Nonstationary spatial dependence structures (since October 2017)
• Co-supervisor, Master thesis of Stanislaus Stadlmann: bamlss.vis: An R Package to Interactively Analyze and Visualize Bayesian Additive Models for Location, Scale and Shape (BAMLSS) Using the Shiny Framework (2017)
• Co-supervisor, Master thesis of Hannes Riebl: Multivariate Quantile Residuals in Copula Regression: Model Evaluation and Selection (2017)
• Co-supervisor, Master thesis of Manuel Carlan: Bayesian Variable Selection (2016)
• Co-supervisor, Master thesis of Paul Wiemann: Statistische Analyse von Advice-Taking (2015)
• Co-supervisor, Master thesis of Manuel Vonrueti: Hyperparameterwahl bei Spike und Slab Prioris für Verteilungsregression (2015)
• Co-supervisor, Master thesis of Anastasia Gorbunova: Statistische Analyse von länderspezifischen Energieprofilen (2015)
• Local organising committee: 29th International Workshop on Statistical Modelling (2014)
• Co-supervisor, Bachelor thesis of Hannes Riebl: Power Law Verteilungen in Generalisierten Additiven Modellen für Lokation, Skala und Form (2014)
• Co-supervisor, Bachelor thesis of Philipp Hanheide: Messung der Armuts-Vulnerabilität (2013)