Bettina Grün: Talks

[1] Bettina Grün, Helga Wagner, and Thomas Petzoldt. Modeling zone diameter measurements to infer antibiotic susceptibility of bacteria. Presented at the “14th Scientific Meeting of the Classification and Data Analysis Group (CLADAG 2023)”, Salerno, Italy, September 11 2023. [ bib ]
[2] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Without pain - mixtures of latent class models with a prior on the number of components. Presented at the “Summer Session of the Working Group on Model-Based Clustering”, Pittsburgh, United States of America, July 17 2023. [ bib ]
[3] Sylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli, and Bettina Grün. Bayesian model-based clustering with the telescoping sampler. Presented at the “15th International Conference of the ERCIM WG on Computational and Methodological Statistics”, London, United Kingdom, December 17 2022. [ bib ]
[4] Bettina Grün and Gertraud Malsiner-Walli. Flexible Bayesian model-based clustering using finite mixtures. Presented at the “Workshop on Statistical Learning and Econometrics: Methodological Advancements and Applications”, Bolzano, Italy, December 12 2022. [ bib ]
[5] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Capturing correlated clusters using mixtures of latent class models. Poster presentation at the “12th European Seminar on Bayesian Econometrics (ESOBE)”, Salzburg, Austria, September 9 2022. [ bib ]
[6] Bettina Grün, Helga Wagner, and Thomas Petzoldt. Estimating the susceptible component of a zone diameter distribution. Presented at the “24th International Conference on Computational Statistics (Compstat 2022)”, Bologna, Italy, August 26 2022. [ bib ]
[7] Bettina Grün. Flexible Bayesian model-based clustering using finite mixtures. Invited talk presented at the “Austrian and Slovenian Statistical Days 2022”, Graz, Austria, April 22 2022. [ bib ]
[8] Bettina Grün, Gertraud Malsiner-Walli, and Sylvia Frühwirth-Schnatter. How many data clusters are in the Galaxy data set? Bayesian cluster analysis in action. Presented online at the “14th International Conference of the ERCIM WG on Computational and Methodological Statistics”, London, United Kingdom, December 19 2021. [ bib ]
[9] Sylvia Frühwirth-Schnatter, Bettina Grün, and Gertraud Malsiner-Walli. Generalized mixtures of finite mixtures and telescoping sampling. Presented at the “Autumn Session of the Working Group on Model-Based Clustering”, Athens, Greece, October 27 2021. [ bib ]
[10] Bettina Grün. Clustering with Bayesian finite mixture models. Presented online at the S3RI Seminar of the Southampton Statistical Sciences Research Institute, University of Southampton, United Kingdom, October 15 2021. [ bib ]
[11] Sylvia Frühwirth-Schnatter, Bettina Grün, and Gertraud Malsiner-Walli. Estimating Bayesian mixtures of finite mixtures with telescoping sampling. Presented online at the “13th Scientific Meeting of Classification and Data Analysis (CLADAG 2021)”, Firenze, Italy, September 11 2021. [ bib ]
[12] Bettina Grün. Advances in model-based clustering. Keynote lecture presented online at the “3rd Insurance Data Science Conference”, City, University of London, United Kingdom, June 18 2021. [ bib ]
[13] Bettina Grün. Different approaches to loss modeling and their impact on risk measure assessment. Presented online at the Research Seminar of the Department of Actuarial Science, University of Lausanne, Switzerland, October 23 2020. [ bib ]
[14] Bettina Grün. Advances in Bayesian model-based clustering. Invited talk presented at the “16th Predictive Analytics Conference”, Vienna, Austria, October 14 2020. [ bib ]
[15] Sylvia Frühwirth-Schnatter, Jan Greve, Bettina Grün, and Gertraud Malsiner-Walli. Model-based clustering with Bayesian Gaussian mixtures. Presented online at the “Workshop on Models and Learning for Clustering and Classification”, September 11 2020. [ bib ]
[16] Bettina Grün. Extending flexmix to model-based clustering with sparse data. Presented lightning talk online at “useR! 2020”, July 2020. [ bib ]
[17] Bettina Grün. Bayesian model-based clustering with flexible and sparse priors. Keynote lecture presented at the “12th Scientific Meeting of Classification and Data Analysis (CLADAG 2019)”, Cassino, Italy, September 13 2019. [ bib ]
[18] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Identifying mixtures of mixtures using Bayesian estimation. Presented in an invited session at “Joint Statistical Meetings (JSM 2019)”, Denver, USA, July 29 2019. [ bib ]
[19] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Bridging finite and infinite mixtures. Presented at the “Summer Session of the Working Group on Model-Based Clustering”, Vienna, Austria, July 15 2019. [ bib ]
[20] Bettina Grün. Tools for model-based clustering in R. Keynote lecture presented at the “useR! 2019”, Toulouse, France, July 12 2019. [ bib ]
[21] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Identifying mixtures of mixtures using Bayesian estimation. Invited talk presented at the “5th Joint Statistical Meeting DAGStat 2019”, Munich, Germany, March 21 2019. [ bib ]
[22] Bettina Grün. Flexible and sparse Bayesian model-based clustering. Presented at the Dipartimento di Statistica, Informatica, Applicazioni “Giuseppe Parenti”, Università degli Studi di Firenze, Florence, Italy, December 19 2018. [ bib ]
[23] Bettina Grün and Gertraud Malsiner-Walli. Bayesian latent class analysis with shrinkage priors: An application to the Hungarian heart disease data. Invited talk presented at the “Second International Conference on Advances in Statistical Modelling of Ordinal Data (ASMOD 2018)”, Naples, Italy, October 26 2018. [ bib ]
[24] Bettina Grün. Prior specification in Bayesian latent class analysis. Invited speed talk presented at the workshop “Challenges for Categorical Data Analysis (CCDA 2018)”, Aachen, Germany, October 23 2018. [ bib ]
[25] Bettina Grün. Discussion of the Invited Papers Session “Prior specifications for finite Bayesian mixture models”. Presented at “Joint Statistical Meetings (JSM 2018)”, Vancouver, Canada, August 2 2018. [ bib ]
[26] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Learning the number of components and data clusters in Bayesian finite mixture models. Presented at “Joint Statistical Meetings (JSM 2018)”, Vancouver, Canada, August 1 2018. [ bib ]
[27] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Learning the number of components and data clusters in Bayesian finite mixture models. Presented at the Research Seminar of the Department of Statistics, Miami University, Oxford, U.S.A., July 24 2018. [ bib ]
[28] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Learning the number of components and data clusters in Bayesian finite mixture models. Presented at the “Summer Session of the Working Group on Model-Based Clustering”, Ann Arbor, U.S.A., July 18 2018. [ bib ]
[29] Bettina Grün. Tools and methods for model-based clustering in R. Invited talk presented at “Septième Rencontres R”, Agrocampus Ouest, Rennes, France, July 5 2018. [ bib ]
[30] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Learning the number of components and data clusters in Bayesian finite mixture models. Presented at the Research Seminar “Empirical Economics and Econometrics”, University of Innsbruck, Innsbruck, Austria, June 26 2018. [ bib ]
[31] Gertraud Malsiner-Walli, Paul Hofmarcher, and Bettina Grün. Semi-parametric regression under model uncertainty in economic applications. Presented at the Research Seminar of the Faculty of Economics, University of Ljubljana, Slovenia, April 23 2018. [ bib ]
[32] Bettina Grün and Sara Dolnicar. Joint model-based clustering for ordinal survey data. Presented at the “10th International Conference of the ERCIM Working Group on Computational and Methodological Statistics”, London, United Kingdom, December 16-18 2017. [ bib ]
[33] Kylie Brosnan, Bettina Grün, and Sara Dolnicar. PC, phone or tablet? Use, preference and completion rates for web surveys. Presented at the PUMA Symposium “Stichprobenverfahren und Repräsentativität - Zufällige und nichtzufällige Auswahltechniken zur Datenerhebung in den Sozialwissenschaften”, Linz, Austria, October 13 2017. [ bib ]
[34] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Inferring components and clusters in Bayesian finite mixture modelling. Poster presentation at the “Summer Session of the Working Group on Model-Based Clustering”, Perugia, Italy, July 18 2017. [ bib ]
[35] Bettina Grün. Mixture models for ordinal data. Invited talk presented at the International Workshop “Alternative Perspectives in Ordinal Data Modelling”, Naples, Italy, October 26 2015. [ bib ]
[36] Bettina Grün and Gertraud Malsiner-Walli. Regularizing finite mixtures of Gaussian distributions. Presented at the “10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG 2015)”, Santa Margherita di Pula, Italy, October 8 2015. [ bib ]
[37] Bettina Grün. Bayesian regularized mixture models. Presented at the “Summer Session of the Working Group on Model-Based Clustering”, Seattle, U.S.A., July 20 2015. [ bib ]
[38] Bettina Grün. Current status and future directions for The R Journal. Presented at the R Summit & Workshop 2015, Copenhagen Business School, Danmark, June 28 2015. [ bib ]
[39] Bettina Grün. Flexible and sparse Bayesian model-based clustering. Presented at the Research Seminar of the Institute of Statistics, Graz University of Technology, Austria, June 19 2015. [ bib ]
[40] Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, and Bettina Grün. Identifying mixtures of mixtures using Bayesian estimation. Invited talk presented at the Conference “Olomoucian Days of Applied Mathematics 2015 (ODAM)”, Palacký University, Olomouc, Czech Republic, May 21 2015. [ bib ]
[41] Bettina Grün. Flexible and sparse Bayesian model-based clustering. Invited talk presented at the Workshop on “Clustering Methods and Their Applications”, Free University of Bozen-Bolzano, Italy, November 28 2014. [ bib ]
[42] Bettina Grün. Flexible and sparse Bayesian model-based clustering. Presented at the “Oberseminar Datenanalyse und Statistik”, University of Augsburg, Germany, October 24 2014. [ bib ]
[43] Bettina Grün. Mixture models for text mining in R. Presented at the 14th Annual Conference of the European Network for Business and Industrial Statistics (ENBIS-14), Johannes Kepler University Linz, Austria, September 23 2014. [ bib ]
[44] Bettina Grün. An introduction to topic modeling. Presented at the Research Seminar of the Digital Data Stream Lab, University of Pavia, Pavia, Italy, April 15 2014. [ bib ]
[45] Kurt Hornik and Bettina Grün. On standard conjugate families for natural exponential families with bounded natural parameter space. Presented at the “11th German Probability and Statistics Days 2014”, Ulm, Germany, March 7 2014. [ bib ]
[46] Bettina Grün, Gertraud Malsiner-Walli, and Sylvia Frühwirth-Schnatter. On prior choice in Bayesian model-based clustering. Presented at the “Summer Session of the Working Group on Model-Based Clustering”, Bologna, Italy, July 26 2013. [ bib ]
[47] Kurt Hornik and Bettina Grün. movMF: An R package for fitting mixtures of von Mises-Fisher distributions. Poster presentation at the “Summer Session of the Working Group on Model-Based Clustering”, Bologna, Italy, July 23 2013. [ bib ]
[48] Martin Ponweiser, Bettina Grün, and Kurt Hornik. Finding scientific topics revisited. Invited talk presented at the “SIS 2013 Statistical Conference: Advances in Latent Variables - Methods, Models and Applications”, Brescia, Italy, June 19 2013. [ bib ]
[49] Bettina Grün. Modeling longitudinal data with finite mixtures of regression models. Presented at the “7th International Workshop on Simulation”, Rimini, Italy, May 23 2013. [ bib ]
[50] Bettina Grün. An introduction to flexible finite mixture modeling. Presented at the Research Seminar of the Department of Mathematical Analysis and Applications of Mathematics, Palacký University, Olomouc, Czech Republic, April 30 2013. [ bib ]
[51] Sara Dolnicar, Bettina Grün, and Friedrich Leisch. Sample size requirements for market segmentation studies. Presented at the “IIBSoR Research Retreat”, Shoalhaven Heads, Australia, February 6 2013. [ bib ]
[52] Bettina Grün. Flexible modeling of mixtures of regressions. Presented at the “Summer Session of the Working Group on Model-Based Clustering”, Guelph, Canada, July 19 2012. [ bib ]
[53] Bettina Grün. Mixture models in text mining. Presented at “FSP Empirical Economics and Econometrics (EmpEc)”, University of Innsbruck, Innsbruck, Austria, March 20 2012. [ bib ]
[54] Bettina Grün and Kurt Hornik. Fitting finite mixtures of von Mises-Fisher distributions using the R package movMF. Presented at the “4th International Conference of the ERCIM Working Group on Computing & Statistics”, London, United Kingdom, December 17-19 2011. [ bib ]
[55] Achim Zeileis, Bettina Grün, and Francisco Cribari-Neto. Beta regression: Shaken, stirred, mixed, and partitioned. Presented at the “useR! 2011”, Warwick, United Kingdom, August 16-18 2011. [ bib ]
[56] Bettina Grün. Mixture models in text mining - Tools in R. Presented at “BioMed-S Retreat”, Schloss Höhenried, Bernried, Germany, July 8 2011. [ bib ]
[57] Bettina Grün and Kurt Hornik. topicmodels: An R package for fitting topic models. Presented at the “3rd International Conference of the ERCIM Working Group on Computing & Statistics”, London, United Kingdom, December 10-12 2010. [ bib ]
[58] Bettina Grün. Finite mixtures of generalized linear regression models. Presented at “FSP Empirical Economics and Econometrics (EmpEc)”, University of Innsbruck, Innsbruck, Austria, October 27 2010. [ bib ]
[59] Bettina Grün and Kurt Hornik. Finite mixture modeling of censored longitudinal data. Presented at “Joint Meeting GfKl-CLADAG”, Florence, Italy, September 8-10 2010. [ bib ]
[60] Bettina Grün. Finite mixtures of generalized linear regression models. Presented at “Séminaire de statistique et économétrie”, GREQAM, Marseille, France, February 23 2010. [ bib ]
[61] Bettina Grün and Friedrich Leisch. Flexible mixture modeling of environmental data and some computational issues. Presented at “IASC-ERS International Summer School on Computational Aspects in Environmental Statistics”, Pamporovo, Bulgaria, September 7-11 2009. [ bib ]
[62] Sara Dolnicar, Bettina Grün, and John R. Rossiter. Choosing the right answer format - Investigating the impact of different answer formats on the results of brand image data. Presented at the School of Management and Marketing Research Seminar, University of Wollongong, Australia, August 5 2009. [ bib ]
[63] Bettina Grün, Paul Hofmarcher, Kurt Hornik, Christoph Leitner, and Stefan Pichler. Extending the latent variable approach to rating model validation - Including finite mixture distributions and censored observations. Presented at the Workshop “Risikomanagment”, Universität Innsbruck, Obergurgl, Austria, April 2-4 2009. [ bib ]
[64] Bettina Grün and Achim Zeileis. Automatic generation of simple (statistical) exams. Presented at the Workshop “R in Teaching and Empirical Research”, Universität für Bodenkultur, Wien, Austria, January 16 2009. [ bib ]
[65] Bettina Grün and Friedrich Leisch. Identification and estimation of finite mixtures of generalized linear models. Presented at “5. Herbstkolloquium des Graduiertenkollegs `Statistische Modellbildung' 2008”, Dortmund, Deutschland, November 28-29 2008. [ bib ]
[66] Bettina Grün. Fitting finite mixtures of linear mixed models with the EM algorithm. Presented at “Compstat 2008”, Porto, Portugal, August 24-29 2008. [ bib ]
[67] Bettina Grün and Friedrich Leisch. FlexMix: Flexible fitting of finite mixtures with the EM algorithm. Presented at the “useR! 2008”, Dortmund, Germany, August 12-14 2008. [ bib ]
[68] Bettina Grün. Comparing variants of the EM algorithm for finite mixtures of linear mixed effects models. Presented at “Joint Statistical Meetings (JSM 2008)”, Denver, U.S.A., August 3-7 2008. [ bib ]
[69] Bettina Grün and Friedrich Leisch. Model diagnostics of finite mixtures using bootstrapping. Presented at the “32nd Annual Conference of the German Classification Society (GfKl)”, Hamburg, Germany, July 16-18 2008. [ bib ]
[70] Bettina Grün and Friedrich Leisch. Finite mixture model diagnostics using the bootstrap. Presented at the “1st Workshop of the ERCIM Working Group on Computing & Statistics”, Neuchâtel, Switzerland, June 19-21 2008. [ bib ]
[71] John R. Rossiter, Bettina Grün, and Sara Dolnicar. A test of Dillon's theory of true (brand-specific) versus artifactual (category-inferred) brand-image attributes. Presented at the “EMAC-ANZMAC BIGMAC4 Research Symposium”, Brighton, U.K., May 30 2008. [ bib ]
[72] Sara Dolnicar, Bettina Grün, and John R. Rossiter. Measuring stability of brand image analysis - Accounting for heterogeneity in descriptive models. Presented at the School of Management and Marketing Research Seminar, University of Wollongong, Australia, January 29 2008. [ bib ]
[73] Bettina Grün, Sara Dolnicar, and John R. Rossiter. Extending Rungie et al.'s model of brand image stability to account for heterogeneity. Presented at the “36th European Marketing Academy Conference (EMAC)”, Reykjavik, Iceland, May 22-25 2007. [ bib ]
[74] Bettina Grün and Friedrich Leisch. Dealing with label switching in finite mixture modelling using constrained clustering. Presented at the “31st Annual Conference of the German Classification Society (GfKl)”, Freiburg, Germany, March 7-9 2007. [ bib ]
[75] Sara Dolnicar and Bettina Grün. The user-friendliness of alternative answer formats. Presented at “ANZMAC 2006”, Brisbane, Australia, December 4-6 2006. [ bib ]
[76] Sara Dolnicar and Bettina Grün. Answer format suitability - The interdependence of answer format and construct measured. Presented at “ANZMAC 2006”, Brisbane, Australia, December 4-6 2006. [ bib ]
[77] Bettina Grün and Friedrich Leisch. Fitting finite mixtures of linear regression models with varying & fixed effects in R. Presented at “Compstat 2006”, Rome, Italy, August 28-September 1 2006. [ bib ]
[78] Bettina Grün and Friedrich Leisch. Finite mixture model diagnostics using the parametric bootstrap. Poster presentation at the “Junior Scientist Conference (JSC)”, Vienna, Austria, April 19-21 2006. [ bib ]
[79] Bettina Grün and Friedrich Leisch. Testing for genuine multimodality in finite mixture models. Presented at the “30th Annual Conference of the German Classification Society (GfKl)”, Berlin, Germany, March 8-10 2006. [ bib ]
[80] Bettina Grün. Identification and estimation of finite mixture models. Presented at the doctoral workshop before the “30th Annual Conference of the German Classification Society (GfKl)”, Berlin, Germany, March 7 2006. [ bib ]
[81] Sara Dolnicar and Bettina Grün. Cross-cultural findings assessing analytic robustness. Presented at the School of Management and Marketing Research Seminar, University of Wollongong, Australia, February 23 2006. [ bib ]
[82] Bettina Grün and Friedrich Leisch. Finite mixture model diagnostics using resampling methods. Presented at the “3rd World Conference on Computational Statistics & Data Analysis”, Limassol, Cyprus, October 28-31 2005. [ bib ]
[83] Bettina Grün and Friedrich Leisch. Analyzing the model fit of finite mixture models. Presented at “Joint Statistical Meetings (JSM 2005)”, Minneapolis, U.S.A., August 7-11 2005. [ bib ]
[84] Sara Dolnicar, Bettina Grün, and Friedrich Leisch. Can the binary answer format improve survey efficiency without substantial information sacrifice? Presented at the School of Management and Marketing Research Seminar, University of Wollongong, Australia, September 23 2004. [ bib ]
[85] Bettina Grün and Friedrich Leisch. Bootstrapping finite mixture models. Presented at “Compstat 2004”, Prague, Czech Republic, August 23-27 2004. [ bib ]
[86] Bettina Grün and Friedrich Leisch. Bootstrapping finite mixture models. Presented at “Statistical Computing 2004”, Schloß Reisensburg, Günzburg, Germany, July 4-7 2004. [ bib ]
[87] Bettina Grün and Friedrich Leisch. BayesMix: An R package for Bayesian mixture modelling. Poster presentation at “useR! 2004”, Vienna, Austria, May 20-22 2004. [ bib ]

Bettina.Gruen@wu.ac.at