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ORCIDSylvia Frühwirth-Schnatter
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Journal Articles
- 2022
[j16]Bettina Grün
, Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter:
How many data clusters are in the Galaxy data set? Adv. Data Anal. Classif. 16(2): 325-349 (2022)- 2021
- [j15]Peter Knaus, Angela Bitto-Nemling, Annalisa Cadonna, Sylvia Frühwirth-Schnatter:
Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP. J. Stat. Softw. 100(13) (2021) - 2019
- [j14]Sylvia Frühwirth-Schnatter, Salvatore Ingrassia, Agustín Mayo-Íscar:
Special issue on "Advances on model-based clustering and classification" - Preface by the Guest Editors. Adv. Data Anal. Classif. 13(1): 1-5 (2019) - [j13]Sylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli:
From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering. Adv. Data Anal. Classif. 13(1): 33-64 (2019) - 2016
- [j12]Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün:
Model-based clustering based on sparse finite Gaussian mixtures. Stat. Comput. 26(1-2): 303-324 (2016) - 2014
- [j11]Cathy W. S. Chen, David B. Dunson, Sylvia Frühwirth-Schnatter, Stephen G. Walker:
Special issue on Bayesian computing, methods and applications. Comput. Stat. Data Anal. 71: 273 (2014) - [j10]Gregor Kastner, Sylvia Frühwirth-Schnatter:
Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models. Comput. Stat. Data Anal. 76: 408-423 (2014) - 2013
- [j9]Agnes Fussl, Sylvia Frühwirth-Schnatter, Rudolf Frühwirth:
Efficient MCMC for Binomial Logit Models. ACM Trans. Model. Comput. Simul. 23(1): 3:1-3:21 (2013) - 2012
- [j8]Jouchi Nakajima, Tsuyoshi Kunihama, Yasuhiro Omori, Sylvia Frühwirth-Schnatter:
Generalized extreme value distribution with time-dependence using the AR and MA models in state space form. Comput. Stat. Data Anal. 56(11): 3241-3259 (2012) - 2011
- [j7]Sylvia Frühwirth-Schnatter:
Panel data analysis: a survey on model-based clustering of time series. Adv. Data Anal. Classif. 5(4): 251-280 (2011) - 2009
- [j6]Sylvia Frühwirth-Schnatter, Rudolf Frühwirth, Leonhard Held, Håvard Rue:
Improved auxiliary mixture sampling for hierarchical models of non-Gaussian data. Stat. Comput. 19(4): 479-492 (2009) - 2008
- [j5]Sylvia Frühwirth-Schnatter, Helga Wagner:
Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling. Comput. Stat. Data Anal. 52(10): 4608-4624 (2008) - [j4]Tatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner:
Neural Network Models for Conditional Distribution Under Bayesian Analysis. Neural Comput. 20(2): 504-522 (2008) - [j3]Sylvia Frühwirth-Schnatter, Regina Tüchler:
Bayesian parsimonious covariance estimation for hierarchical linear mixed models. Stat. Comput. 18(1): 1-13 (2008) - 2007
- [j2]Sylvia Frühwirth-Schnatter, Rudolf Frühwirth:
Auxiliary mixture sampling with applications to logistic models. Comput. Stat. Data Anal. 51(7): 3509-3528 (2007) - 2006
- [j1]Tatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner:
Bayesian testing for non-linearity in volatility modeling. Comput. Stat. Data Anal. 51(3): 2029-2042 (2006)
Conference and Workshop Papers
- 2002
- [c1]Sylvia Frühwirth-Schnatter, Leopold Sögner:
Bayesian Estimation of the Heston Stochastic Volatility Model. OR 2002: 480-485
Coauthor Index
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