Sylvia Frühwirth-Schnatter

18 papers Journal 17Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Cover it up! Bipartite graphs uncover identifiability in sparse factor analysis.
J. Multivar. Anal.
Darjus Hosszejni, Sylvia Frühwirth-Schnatter
2022 J jnl
How many data clusters are in the Galaxy data set?
Adv. Data Anal. Classif.
Bettina Grün, Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter
2021 J jnl
Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP.
J. Stat. Softw.
Peter Knaus, Angela Bitto-Nemling, Annalisa Cadonna, Sylvia Frühwirth-Schnatter
2019 J jnl
From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering.
Adv. Data Anal. Classif.
Sylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli
2019 J jnl
Special issue on "Advances on model-based clustering and classification" - Preface by the Guest Editors.
Adv. Data Anal. Classif.
Sylvia Frühwirth-Schnatter, Salvatore Ingrassia, Agustín Mayo-Íscar
2016 J jnl
Model-based clustering based on sparse finite Gaussian mixtures.
Stat. Comput.
Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün
2014 J jnl
Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models.
Comput. Stat. Data Anal.
Gregor Kastner, Sylvia Frühwirth-Schnatter
2014 J jnl
Special issue on Bayesian computing, methods and applications.
Comput. Stat. Data Anal.
Cathy W. S. Chen, David B. Dunson, Sylvia Frühwirth-Schnatter, Stephen G. Walker
2013 J jnl
Efficient MCMC for Binomial Logit Models.
ACM Trans. Model. Comput. Simul.
Agnes Fussl, Sylvia Frühwirth-Schnatter, Rudolf Frühwirth
2012 J jnl
Generalized extreme value distribution with time-dependence using the AR and MA models in state space form.
Comput. Stat. Data Anal.
Jouchi Nakajima, Tsuyoshi Kunihama, Yasuhiro Omori, Sylvia Frühwirth-Schnatter
2011 J jnl
Panel data analysis: a survey on model-based clustering of time series.
Adv. Data Anal. Classif.
Sylvia Frühwirth-Schnatter
2009 J jnl
Improved auxiliary mixture sampling for hierarchical models of non-Gaussian data.
Stat. Comput.
Sylvia Frühwirth-Schnatter, Rudolf Frühwirth, Leonhard Held, Håvard Rue
2008 J jnl
Bayesian parsimonious covariance estimation for hierarchical linear mixed models.
Stat. Comput.
Sylvia Frühwirth-Schnatter, Regina Tüchler
2008 J jnl
Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling.
Comput. Stat. Data Anal.
Sylvia Frühwirth-Schnatter, Helga Wagner
2008 J jnl
Neural Network Models for Conditional Distribution Under Bayesian Analysis.
Neural Comput.
Tatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner
2007 J jnl
Auxiliary mixture sampling with applications to logistic models.
Comput. Stat. Data Anal.
Sylvia Frühwirth-Schnatter, Rudolf Frühwirth
2006 J jnl
Bayesian testing for non-linearity in volatility modeling.
Comput. Stat. Data Anal.
Tatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner
2002 — conf
Bayesian Estimation of the Heston Stochastic Volatility Model.
OR
Sylvia Frühwirth-Schnatter, Leopold Sögner