Details

Titel: Bayesian statistics and MCMC methods

Kurzfassung: The Bayesian paradigm provides a coherent and unified approach to problems of statistical inference such as parameter estimation, hypothesis testing, prediction, or model discrimination within a decision-theoretic framework. Bayesian inference for complex models heavily relies on computationally intensive methods. At the IFAS we are currently working on Bayesian modelling of categorical and mixed data, Bayesian estimation of mixture and treatment effects models, Bayesian model selection and approximate Bayesian computation for models with intractable likelihoods.

Web: Homepage des IFAS

Projektbeginn: 01.01.2012

Projektende: 31.12.2025

Beteiligte Personen

LeiterInnen: Assoz.Univprof. Mag. Dr. Helga Wagner

MitarbeiterInnen: Dr. M.Stat. Markus Hainy

Forschungseinheiten der JKU

34% Abteilung für Datenanalyse und Ökonometrie

33% Abteilung für Medizinische Statistik und Biometrie

33% Abteilung für Datengewinnung und Datenqualität

Wissenschaftszweige

101018 Statistik | 101024 Wahrscheinlichkeitstheorie | 101029 Mathematische Statistik | 102009 Computersimulation | 509 Andere Sozialwissenschaften | 5701 Angewandte Statistik

Publikationen

• Pfeiler R., Wagner H.:
  Shrinkage in a Bayesian Panel Data Model with Time-Varying Coefficients, in Jochen Einbeck, Hyeyoung Maeng, Emmanuel Ogundimu, Konstantinos Perrakis: Developments in Statistical Modelling , Springer, Cham, Schweiz, Seite(n) 109-115, 2024
• Wagner H., Malsiner Walli G., Hofmarcher P.:
  Bayesianische Modellwahl, in Jan Gertheiss und Matthias Schmid: Moderne Verfahren der Angewandten Statistik, Springer, Seite(n) 30, 2024
• Wagner H., Frühwirth-Schnatter S., Jacobi L.:
  Factor-augmented Bayesian treatment effects models for panel outcomes, in E.J. Kontoghiorghes, A.M. Colubi, M. Deistler, in Econometrics and Statistics, Vol. 28, Elsevier, Seite(n) 63-80, 2023
• Hainy M., Price D., Restif O., Drovandi C.:
  Optimal Bayesian design for model discrimination via classification, in Statistics and Computing, Vol. 32, Nummer 2, 2022
• Klein N., Carlan M., Kneib T., Lang S., Wagner H.:
  Bayesian Effect Selection in Structured Additive Distributional Regression Models, in Bayesian Analysis, Nummer 16, Seite(n) 545-573, 2021
• Taniguchi S., Bertl J., Futschik A., Kishino H., Okazaki T.:
  Waves out of the Korean Peninsula and inter- and intra-species replacements in freshwater fishes in Japan, in Genes, Vol. 12, Nummer 2, Seite(n) 303, 2021
• Wiemann P., Kneib T., Wagner H.:
  Effect Selection and Regularization in Structured Additive Distributional Regression, in Marina Vanucci und Mahlet Tadesse: Handbook of Bayesian Variable Selection, Chapman and Hall, 2021
• Moffat H., Hainy M., Papanikolaou N., Drovandi C.:
  Sequential experimental design for predator-prey functional response experiments, in Journal of The Royal Society Interface, Vol. 17, Nummer 166, 2020
• Föckersperger T., Wagner H.:
  Modeling Mothers’ yearly earnings after returning from maternity leave with a Bayesian distributional regression model: Proceedings of the 35th International Workshop on Statistical Modelling, Seite(n) 333-336, 2020
• Pauger D., Wagner H.:
  Bayesian Effect Fusion for Categorical Predictors, in Bayesian Analysis, Vol. 14, Nummer 2, Seite(n) 341-369, 2019
• Malsiner Walli G., Pauger D., Wagner H.:
  Effect fusion using model-based clustering, in Statistical Modelling, Vol. 18, Nummer 2, Seite(n) 175-196, 2018
• Wagner H., Leitner M.:
  Bayesian Effect fusion for Categorical Predictors in Logistic Regression: Proceedings of the 33th International Workshop on Statistical modelling, Vol. 1, Seite(n) 183-188, 2018
• Klein N., Carlan M., Kneib T., Lang S., Wagner H.:
  Effect Selection in Distributional Regression: Proceedings of the 33rd International Workshop on Statistical Modelling, Vol. 1, Seite(n) 157–162, 2018
• Malsiner Walli G., Frühwirth-Schnatter S., Grün B.:
  Identifying mixtures of mixtures using Bayesian estimation, in Journal of Computational and Graphical Statistics, Vol. 26, Nummer 2, Seite(n) 285-295, 2017
• Wagner H., Frühwirth-Schnatter S.:
  Bayesian Inference for Mixed Effects Multinomial Logits Models: International Workshop on Statistical Modelling 2017, Vol. 1, Seite(n) 246- 251, 2017
• Frühwirth-Schnatter S., Wagner H., Jacobi L.:
  Kind oder Karriere? Was Müttern die Auszeit kostet, 2017
• Wagner H., Pauger D.:
  Discussion: Bayesian regularization and effect fusion for categorical predictors, in Statistical Modelling, Vol. 16, Nummer 3, Seite(n) 220-227, 2016
• Hainy M., Müller W., Wagner H.:
  Likelihood-free simulation-based optimal design with an application to spatial extremes, in Stochastic Environmental Research and Risk Assessment, Vol. 30, Nummer 2, Seite(n) 481-492, 2016
• Malsiner Walli G., Frühwirth-Schnatter S., Grün B.:
  Model-based clustering based on sparse finite Gaussian mixtures, in Statistics and Computing, Vol. 26, Seite(n) 303-324, 2016
• Dvorzak M., Wagner H.:
  Sparse Bayesian modelling of underreported count data, in Statistical Modelling, Nummer 1, Seite(n) 24-46, 2016
• Jacobi L., Wagner H., Frühwirth-Schnatter S.:
  Bayesian treatment effects models with variable selection for panel outcomes with an application to earnings effects of maternity leave, in Journal of Econometrics, Vol. 193, Nummer 1, Seite(n) 234-250, 2016
• Pauger D., Malsiner Walli G., Wagner H.:
  Bayesian effect fusion for categorical predictors with sparse finite mixture prior: Proceedings of the 31st International Workshop on Statistical Modelling, Vol. 1, Seite(n) 247-252, 2016
• Müller W., Wynn H.:
  Controlled Versus "Random" Experiments: A Principle, in Kunert, Joachim and Müller, Christine H. and Atkinson, Anthony C.: mODa 11 - Advances in Model-Oriented Design and Analysis, Serie Contributions to Statistics, Springer International Publishing, Seite(n) 191-198, 2016
• Hainy M., Drovandi C., McGree J.:
  Likelihood-Free Extensions for Bayesian Sequentially Designed Experiments: mODa 11 – Advances in Model-Oriented Design and Analysis. Proceedings of the 11th International Workshop in Model-Oriented Design and Analysis held in Hamminkeln, Germany, June 12-17, 2016, Serie Contributions to Statistics, Springer International Publishing, Seite(n) 153-161, 2016
• Pauger D., Wagner H.:
  A comparison of different priors for sparse Bayesian modelling in regression models with ordinal predictors: Proceedings of the 30th International Workshop on Statistical Modelling, Vol. 2, Seite(n) 215-218, 2015
• Hainy M., Drovandi C.:
  Approximate Bayesian computation for spatial extremes using composite score functions, in Friedl, H., Wagner, H.: Proceedings of the 30th International Workshop on Statistical Modelling, Volume 2, Seite(n) 111-114, 2015
• Friedl H., Wagner H.:
  Proceedings of the 30th International Workshop on Statistical Modelling Vol. 1 & 2, 2015
• Hainy M.:
  Simulation-based optimal experimental design for models with intractable likelihoods using likelihood-free methods, 2015
• Hainy M., Müller W., Wynn H.:
  Learning Functions and Approximate Bayesian Computation Design: ABCD, in Entropy, Vol. 16, Nummer 8, Seite(n) 4353-4374, 2014
• Hornik K., Grün B.:
  On Standard Conjugate Families for Natural Exponential Families With Bounded Natural Parameter Space, in Journal of Multivariate Analysis, Vol. 126, Seite(n) 14-24, 2014
• Wagner H., Tüchler R.:
  A Comparison of Bayesian Mixed Data Models for Austrian SILC data, in Austrian Journal of Statistics, Vol. 43, Nummer 2, Seite(n) 103-117, 2014
• Duller C., Pauger D., Wagner H.:
  Formalization of Management Accounting: A Bayesian Approach, in International Journal of Strategic Management, Vol. 14, Nummer 2, Seite(n) 7-12, 2014
• Pauger D., Wagner H.:
  Bayesian Effect Fusion for Categorical and Ordinal Predictors: Proceedings of the 29th International Workshop on Statistical Modelling, Seite(n) 261-267, 2014
• Hainy M., Müller W., Wagner H.:
  Likelihood-Free Simulation-Based Optimal Design: An Introduction, in Melas, Viatcheslav B.; Mignani, Stefania; Monari, Paola; Salmaso, Luigi: Topics in Statistical Simulation, Serie Springer Proceedings in Mathematics & Statistics, Vol. 114, Seite(n) 271-278, 2014
• Hainy M.:
  Efficient MCMC Estimation of Mixed Effects Binary Logit Models. Comparison of Various Markov Chain Monte Carlo Estimation Techniques, Akademikerverlag, Saarbrücken, 2014
• Grün B., Malsiner Walli G.:
  Discussion of ``How to Find an Appropriate Clustering for Mixed-Type Variables with Applicationto Socio-Economic Stratification'' by Hennig and Liao, in Journal of the Royal Statistical Society, Series C (Applied Statistics), Vol. 62, Nummer 3, Seite(n) 350-351, 2013
• Fussl A., Frühwirth-Schnatter S., Frühwirth R.:
  Efficient MCMC for Binomial Logit Models, in ACM Transactions on Modeling and Computer Simulation, Vol. 23, Nummer 1, Seite(n) 1-21, 2013
• Hornik K., Grün B.:
  On Conjugate Families and Jeffreys Priors for von Mises-Fisher, in Journal of Statistical Planning and Inference, Vol. 143, Nummer 5, Seite(n) 992-999, 2013
• Pauger D., Duller C., Wagner H.:
  Analysing formalisation of management accounting by Bayesian variable selection in a cumulative logit model: Proceedings of the 28th International Workshop on Statistical Modeling, Seite(n) 731-734, 2013
• Hainy M., Müller W., Wynn H.:
  Approximate Bayesian Computation Design (ABCD), an Introduction, in Ucinski, Dariusz; Atkinson, Anthony C.; Patan, Maciej: mODa 10 – Advances in Model-Oriented Design and Analysis, Proceedings of the 10th International Workshop in Model-Oriented Design and Analysis Held in Łagów Lubuski, Poland, June 10–14, 2013, Serie Contributions to Statistics, Springer International Publishing, Springer, Seite(n) 135-143, 2013
• Wagner H., Tüchler R.:
  Bayesian Factorization Model for analysing mixed data: Proceedings of the 28th International Workshop on Statistical Modeling, Seite(n) 441-446, 2013
• Dvorzak M., Wagner H.:
  Sparse Bayesian Modelling of underreported count data: Proceedings of the 28th International Workshop on Statistical Modeling, Seite(n) 127-132, 2013
• Hainy M., Müller W., Wagner H.:
  Likelihood-free Simulation-based Optimal Design, Serie IFAS Research Paper Series, Vol. 64, IFAS Eigenverlag, Linz, 2013
• Wagner H., Duller C.:
  Bayesian model selection for logistic regression models with random intercept, in Computational Statistics and Data Analysis, Vol. 56, Nummer 5, Seite(n) 1256-1275, 2012
• Tüchler R., Wagner H.:
  Analysing living conditions in Austria by a Bayesian mixed data model: Proceedings of the 27th International Workshop on Statistical Modelling, Vol. 1, Seite(n) 321-326, 2012
• Stehlik M., Pant B., Pant K., Pardasani K.:
  Issues on Machine Learning for Prediction of Classes Among Molecular Sequences of Plants and Animals, in Theodore E. Simos, George Psihoyios, Ch. Tsitouras, Zacharias Anastassi: NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied, Vol. 1479, Seite(n) 446-449, 2012
• Duller C.:
  Model selection for logistic regression models: AIP Conference Proceedings, Vol. 1479, Seite(n) 414-416, 2012
• Stehlik M.:
  Preface for the "Symposium on statistics and modeling III", in Theodore E. Simos, George Psihoyios, Ch. Tsitouras, Zacharias Anastassi: NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied, Vol. 1479, Seite(n) 412-414, 2012
• Hainy M., Müller W., Wagner H.:
  Simulation-based DB-optimal designs: conception and implementation issues, in Komárek, A., Nagy, S.: Proceedings of the 27th International Workshop on Statistical Modelling, Seite(n) 537-542, 2012
• Fussl A.:
  R package: binomlogit, 2012
• Pamminger C.:
  R-package: bayesMCClust, 2012
• Malsiner Walli G.:
  Bayesian Variable Selection in Normal Regression Models, 2010

Vorträge

• Network inference in a stochastic multi-population neural mass model via approximate Bayesian computation, Germany, 28.11.2024
• Network inference in a stochastic multi-population neural mass model via approximate Bayesian computation, Austria, 05.09.2024
• Network inference in a stochastic multi-population neural mass model via approximate Bayesian computation, United Kingdom of Great Britain and Northern Ireland, 06.06.2024
• Flexible Bayesian Treatment effects for panel outcomes, Austria, 18.04.2024
• Shrinkage in a Bayesian Panel Data Model with Time-Varying Coefficients, United Kingdom of Great Britain and Northern Ireland, 18.07.2024
• Flexible Bayesian Treatment effects for panel outcomes, Italy, 05.07.2024
• Detecting selection using signature kernels: A novel method for multi-locus Wright-Fisher models with recombination, France, 18.06.2024
• Shrinkage in a Bayesian random intercept model with time-varying coefficients, Austria, 03.04.2024
• Haplotype reconstruction via Bayesian linear models with unknown design, Austria, 31.08.2023
• Statistical inference of selection coefficient from temporal allele frequencies, Austria, 31.08.2023
• Haplotype reconstruction via Bayesian linear models with unknown design, Japan, 01.08.2023
• Statistical inference of selection coefficient from temporal allele frequencies, Japan, 01.08.2023
• Shrinkage of time-varying effects in panel data models, Italy, 11.09.2023
• Active Discrimination Learning, Austria, 22.04.2022
• Factor-augmented Bayesian Treatment Effect Models for Panel Outcomes, Austria, 22.04.2022
• Joint Likelihood-free Inference of Number of Selected SNPs and Selection Coefficient in an Evolving Population, Austria, 22.04.2022
• Sparse Bayesian Unbounded Linear Models with Unknown Design over Finite Alphabets, Austria, 22.04.2022
• Bayesian design for parameter estimation using supervised regression methods, Austria, 13.04.2022
• Joint likelihood-free inference of number of selected snps and selection coefficient in an evolving population, United Kingdom of Great Britain and Northern Ireland, 29.03.2022
• Sparse Bayesian Unbounded Linear Models with Unknown Design over Finite Alphabets, United Kingdom of Great Britain and Northern Ireland, 29.03.2022
• Shrinkage of time-varying effects in panel data models, Austria, 19.12.2021
• Bayesian approaches to treatment effects modelling, Austria, 03.09.2021
• A flexible Bayesian model for treatment effects on panel outcomes, Austria, 08.02.2021
• A flexible Bayesian model for treatment effects on panel outcomes, Austria, 19.01.2021
• Bayesian model discrimination design for models with intractable likelihoods via supervised classification methods, Austria, 07.09.2021
• Bayesian model discrimination design for models with intractable likelihoods via supervised classification methods, Austria, 05.03.2021
• Bayesian modelling of treatment effects on panel outcomes, Austria, 28.11.2020
• Achieving Sparsity in Bayesian Regression Models, Germany, 04.02.2020
• Flexible Bayesian modelling of treatment effects on panel outcomes, Austria, 21.12.2020
• Bayesian model discrimination design for models with intractable likelihoods via supervised classification methods, Austria, 28.11.2020
• Sparse Bayesian Modelling, Germany, 07.10.2019
• Bayesian modelling of treatment effects on panel outcomes, Slovenia, 27.09.2019
• Bayesian Model-Based Clustering with Flexible and Sparse Priors, Italy, 13.09.2019
• Introduction to Bayesian Statistics, Austria, 05.08.2019
• Identifying Mixtures of Mixtures using Bayesian Estimation, United States of America, 29.07.2019
• Identifying Mixtures of Mixtures using Bayesian Estimation, Germany, 21.03.2019
• Bayesian effect fusion for categorical predictors, Austria, 22.02.2019
• Bayesian effect selection in structured additive distributional regression models, Austria, 28.11.2019
• Bayesian modelling of treatment effects on panel outcomes, Germany, 24.06.2019
• Optimal Bayesian design for models with intractable likelihoods via supervised learning methods, United Kingdom of Great Britain and Northern Ireland, 16.12.2019
• Bayesian Effect Selection in Structured Additive Distributional Regression Models, Switzerland, 10.09.2019
• Optimal Bayesian design for models with intractable likelihoods via supervised learning methods, Austria, 05.09.2019
• Optimal Bayesian design for models with intractable likelihoods via supervised learning methods, Slovakia, 27.06.2019
• Optimal Bayesian design for models with intractable likelihoods via supervised learning methods, United States of America, 20.05.2019
• Sequential experimental design for functional response experiments, Austria, 24.04.2019
• A flexible Bayesian model for treatment effects on panel outcomes, Germany, 20.03.2019
• Optimal Bayesian design for model discrimination via classification, Germany, 20.03.2019
• Bridging Finite and Infinite Mixtures, Austria, 15.07.2019
• Introduction to Bayesian Exercises, Austria, 06.08.2019
• Optimal Bayesian design for models with intractable likelihoods via supervised learning methods, Austria, 09.05.2019
• A flexible Bayesian model for treatment effects on panel outcomes, Italy, 18.12.2018
• Discussion of the Invited Papers Session "Prior Specifications for Finite Bayesian Mixture Models", Canada, 02.08.2018
• Learning the Number of Components and Data Clusters in Bayesian Finite Mixture Models, United States of America, 24.07.2018
• Semi-Parametric Regression Under Model Uncertainty in, Slovenia, 23.04.2018
• Refined Measures Of Dynamic Connectedness Based On Time-Varying Parameter Vector Autoregressions, Italy, 16.12.2018
• Bayesian Effect fusion for Categorical Predictors in Logistic Regression, Italy, 14.12.2018
• Bayesian Effect fusion for Categorical Predictors in Logistic Regression, Austria, 13.09.2018
• Bayesian Effect fusion for Categorical Predictors in Logistic Regression, United Kingdom of Great Britain and Northern Ireland, 17.07.2018
• Learning the Number of Components and Data Clusters in Bayesian Finite Mixture Models, Canada, 01.08.2018
• Learning the Number of Components and Data Clusters in Bayesian Finite Mixture Models, United States of America, 18.07.2018
• Bayesian effect fusion for categorical predictors, Australia, 13.11.2017
• Sparse Bayesian Modelling, Germany, 23.07.2017
• Bayesian Inference for Mixed Effects Multinomial Logits Models, Netherlands, 06.07.2017
• Inferring Components and Clusters in Bayesian Finite Mixture, Italy, 18.07.2017
• Warum Bayes?, Austria, 16.12.2016
• Likelihood-Free Extensions for Bayesian Sequentially Designed Experiments, Taiwan, Province of China, 17.12.2016
• Bayesian effect fusion for categorical predictors, Austria, 29.11.2016
• ABCD: Approximate Bayesian Computing Design, United Kingdom of Great Britain and Northern Ireland, 01.06.2016
• Sparse Bayesian Modelling for Categorical Predictors, Austria, 28.04.2016
• Sparse Bayesian modelling for categorical predictors, Spain, 10.12.2016
• Sparse Bayesian modelling for categorical predictors, Spain, 10.12.2016
• Effect fusion using sparse finite mixtures, France, 19.07.2016
• Finite Mixture Priors for Sparse Bayesian Modelling, France, 05.07.2016
• Likelihood-Free Extensions for Bayesian Sequentially Designed Experiments, Germany, 17.06.2016
• Bayesian Inference for Mixed Effects Multinomial Logit Models, Italy, 15.06.2016
• Sparse Bayesian Modelling for Categorical Predictors, Germany, 18.03.2016
• Sparse Bayesian Modelling for Categorical Predictors with spike and slab priors, Italy, 16.06.2016
• Effect fusion using sparse finite mixtures, Italy, 15.06.2016
• Flexible and Sparse Bayesian Model-Based Clustering, Austria, 19.06.2015
• Sparse Bayesian Modelling for Categorical Predictors, Austria, 02.06.2015
• Big Design: Versuchsplanung in Zeiten der Datenflut, Austria, 25.05.2015
• Sparse Bayesian Modelling with Spike and Slab Priors, Germany, 22.04.2015
• Fusion kategorialer Effekte in Regressionsmodellen, Austria, 20.04.2015
• Sparse Bayesian Modelling for Categorical Predictors, United Kingdom of Great Britain and Northern Ireland, 12.12.2015
• Sparse Bayesian Modelling for Categorical Predictors, Switzerland, 30.10.2015
• Approximate Bayesian computation for spatial extremes using composite score functions, Austria, 21.10.2015
• Sparse Bayesian Modelling for Categorical Predictors, Austria, 17.10.2015
• Regularizing Finite Mixtures of Gaussian Distributions, Italy, 08.10.2015
• ABCD: an Introduction, Austria, 22.09.2015
• Sparse Bayesian Modelling for Categorical Predictors, Germany, 16.09.2015
• Sparse Bayesian modeling for categorical predictors, Greece, 26.06.2015
• Bayesian variable selection in semi-parameteric growth regression, Austria, 28.05.2015
• Identifying Mixtures of Mixtures Using Bayesian Estimation, Czech Republic, 21.05.2015
• Approximate Bayesian Computation Design with an Application to Spatial Extremes, Austria, 22.09.2015
• Bayesian variable selection in semi-parameteric growth regression, Switzerland, 30.10.2015
• Approximate Bayesian computation for spatial extremes using composite score functions, Austria, 07.07.2015
• Bayesian variable selection in semi-parameteric growth regression, Austria, 07.07.2015
• Flexible and Sparse Bayesian Model-Based Clustering, Italy, 28.11.2014
• Bayesian Effect Fusion for Categorical and Ordinal Predictors, Germany, 17.09.2014
• Sparse Bayesian Modelling with Spike and Slab Priors, Germany, 25.03.2014
• Flexible and Sparse Bayesian Model-Based Clustering, Germany, 24.10.2014
• Sparse Bayesian Modelling with Spike and Slab Priors, Germany, 11.06.2014
• Approximate Bayesian Computation Design with an Application to Spatial Extremes, Austria, 24.09.2014
• Bayesian Effect Fusion for Categorical Predictors, Austria, 22.09.2014
• Bayesian Effect Fusion for Categorical Predictors, Austria, 19.09.2014
• Likelihood-free Simulation-based Optimal Design with an Application to Spatial Extremes, Austria, 19.09.2014
• Bayesian Effect Fusion for Categorical Predictors, Austria, 11.09.2014
• Simulation-based Likelihood-free Optimal Designs, Austria, 11.09.2014
• Bayesian Effect Fusion for Categorical and Ordinal Predictors, Germany, 16.07.2014
• Formalization of Management Accounting: A Bayesian Approach, Italy, 29.06.2014
• Bayesian Treatment Effects Models with Variable Selection for Panel Outcomes with an Application to Earnings effects of Maternity Leave, United Kingdom of Great Britain and Northern Ireland, 28.06.2014
• On Standard Conjugate Families for Natural Exponential Families with Bounded Natural Parameter Space, Germany, 07.03.2014
• Sparse Bayesian treatment effects models for panel outcomes, Germany, 04.03.2014
• Likelihood-free Simulation-based Optimal Design with an Application to Spatial Extremes, Italy, 07.12.2014
• Investigating the influence of different prior choices for mixtures of Gaussian mixtures, Austria, 19.09.2014
• Investigating the influence of difference priors choices for mixtures of Gaussian mixtures, Italy, 03.09.2014
• Identifying Mixtures of Mixtures Using Bayesian Estimation, Mexico, 16.07.2014
• Likelihood-free Simulation-based Optimal Design, Austria, 25.10.2013
• Identifying mixtures of mixtures using Bayesian estimation, Netherlands, 17.07.2013
• A Bayesian Factorization Model for Analysing Mixed Data, Italy, 11.07.2013
• Approximate Bayesian Computation Design (ABCD), an Introduction, Poland, 13.06.2013
• Identifying mixtures of mixtures using Bayesian estimation, Italy, 06.06.2013
• Last Night a Shrinkage Saved My Life: Economic Growth, Model Uncertainty and Correlated Regressors, Spain, 06.06.2013
• Likelihood-free simulation-based optimal Bayesian design, Hungary, 12.10.2013
• Efficient Data-augmented MCMC Methods for Binomial Logit Models, Austria, 11.09.2013
• Analysing formalisation of management accounting by Bayesian variable selection in a cumulative logit model, Italy, 18.06.2013
• Deriving consensus ratings of the big three rating agencies, Austria, 28.05.2013
• Likelihood-free Simulation-based Optimal Design, Italy, 22.05.2013
• Association Rules in BMA or Jointness of Growth Determinantes, Austria, 13.05.2013
• Bayesian estimation of a discrete choice model for household labor supply in Austria, Austria, 08.05.2013
• Identifying mixtures of mixtures using Bayesian estimation, Italy, 23.07.2013
• Analysing formalisation of management Accounting by Bayesian variable selection in a cumulative logit model, Italy, 11.07.2013
• Bayesian estimation of a discrete choice model for household labor supply in Austria, Italy, 09.07.2013
• Likelihood-free simulation-based optimal design, France, 01.07.2013
• Bayesian model selection with spike and slab priors, Germany, 12.11.2012
• Bayesian treatment effects models for panel outcomes, Japan, 27.06.2012
• Bayesian treatment effects models for panel outcomes with variable selection, Austria, 27.02.2012
• Bayesian Treatment effects for Panel outcomes, Austria, 09.05.2012
• Model-based clustering based on sparse finite Gaussian mixtures, Spain, 02.12.2012
• Sparse Bayesian modelling of treatment effects on panel outcomes - Analysis of Labor Market Effects of a Mother’s Time spent at Home after Childbirth, Austria, 01.11.2012
• Analysing living conditions in Austria by a Bayesian mixed data model, Austria, 20.09.2012
• Model selection for logistic regression models, Greece, 20.09.2012
• Model-based clustering based on sparse finite Gaussian mixtures, Italy, 06.09.2012
• Analysing living conditions in Austria by a Bayesian mixed data model, Czech Republic, 16.07.2012
• Simulation-Based Optimal Bayesian Designs: Applications and Extensions, Austria, 18.09.2012
• Efficient Data-augmented MCMC Methods for Binomial Logit Models, Austria, 01.11.2012
• Efficient MCMC Estimation of Mixed Effects Binary Logit Models, Austria, 01.11.2012
• Model-based clustering based on sparse finite Gaussian mixtures, Austria, 01.11.2012
• Simulation-based DB-optimal designs: Conception and implementation issues, Czech Republic, 17.07.2012
• Efficient MCMC Methods for Estimating Binomial Logit Models, Japan, 26.06.2012
• Bayesian treatment effects models for panel outcomes with variable selection, United Kingdom of Great Britain and Northern Ireland, 19.12.2011