Sylvia Frühwirth-Schnatter

According to our database, Sylvia Frühwirth-Schnatter authored at least 17 papers between 2002 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2022

How many data clusters are in the Galaxy data set?

Bettina Grün, Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter

Adv. Data Anal. Classif., 2022

2021

Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP.

Peter Knaus, Angela Bitto-Nemling, Annalisa Cadonna, Sylvia Frühwirth-Schnatter

J. Stat. Softw., 2021

2019

From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering.

Sylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli

Adv. Data Anal. Classif., 2019

Special issue on "Advances on model-based clustering and classification" - Preface by the Guest Editors.

Sylvia Frühwirth-Schnatter, Salvatore Ingrassia, Agustín Mayo-Íscar

Adv. Data Anal. Classif., 2019

2016

Model-based clustering based on sparse finite Gaussian mixtures.

Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün

Stat. Comput., 2016

2014

Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models.

Gregor Kastner, Sylvia Frühwirth-Schnatter

Comput. Stat. Data Anal., 2014

Special issue on Bayesian computing, methods and applications.

Cathy W. S. Chen, David B. Dunson, Sylvia Frühwirth-Schnatter, Stephen G. Walker

Comput. Stat. Data Anal., 2014

2013

Efficient MCMC for Binomial Logit Models.

Agnes Fussl, Sylvia Frühwirth-Schnatter, Rudolf Frühwirth

ACM Trans. Model. Comput. Simul., 2013

2012

Generalized extreme value distribution with time-dependence using the AR and MA models in state space form.

Jouchi Nakajima, Tsuyoshi Kunihama, Yasuhiro Omori, Sylvia Frühwirth-Schnatter

Comput. Stat. Data Anal., 2012

2011

Panel data analysis: a survey on model-based clustering of time series.

Sylvia Frühwirth-Schnatter

Adv. Data Anal. Classif., 2011

2009

Improved auxiliary mixture sampling for hierarchical models of non-Gaussian data.

Sylvia Frühwirth-Schnatter, Rudolf Frühwirth, Leonhard Held, Håvard Rue

Stat. Comput., 2009

2008

Bayesian parsimonious covariance estimation for hierarchical linear mixed models.

Sylvia Frühwirth-Schnatter, Regina Tüchler

Stat. Comput., 2008

Neural Network Models for Conditional Distribution Under Bayesian Analysis.

Tatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner

Neural Comput., 2008

Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling.

Sylvia Frühwirth-Schnatter, Helga Wagner

Comput. Stat. Data Anal., 2008

2007

Auxiliary mixture sampling with applications to logistic models.

Sylvia Frühwirth-Schnatter, Rudolf Frühwirth

Comput. Stat. Data Anal., 2007

2006

Bayesian testing for non-linearity in volatility modeling.

Tatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner

Comput. Stat. Data Anal., 2006

2002

Bayesian Estimation of the Heston Stochastic Volatility Model.

Sylvia Frühwirth-Schnatter, Leopold Sögner

Proceedings of the Operations Research Proceedings 2002, 2002