Sylvia Frühwirth-Schnatter - researchr alias

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Viewing Publication 1 - 16 from 16

2022

How many data clusters are in the Galaxy data set?Bettina Grün, Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter. adac, 16(2):325-349, 2022. [doi]

2021

Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVPPeter Knaus, Angela Bitto-Nemling, Annalisa Cadonna, Sylvia Frühwirth-Schnatter. jstatsoft, 100(13), 2021. [doi]

2019

From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clusteringSylvia Frühwirth-Schnatter, Gertraud Malsiner-Walli. adac, 13(1):33-64, 2019. [doi]

Special issue on "Advances on model-based clustering and classification" - Preface by the Guest EditorsSylvia Frühwirth-Schnatter, Salvatore Ingrassia, Agustín Mayo-Íscar. adac, 13(1):1-5, 2019. [doi]

2016

Model-based clustering based on sparse finite Gaussian mixturesGertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter, Bettina Grün. sac, 26(1-2):303-324, 2016. [doi]

2014

Special issue on Bayesian computing, methods and applicationsCathy W. S. Chen, David Dunson, Sylvia Frühwirth-Schnatter, Stephen G. Walker. csda, 71:273, 2014. [doi]

Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility modelsGregor Kastner, Sylvia Frühwirth-Schnatter. csda, 76:408-423, 2014. [doi]

2013

Efficient MCMC for Binomial Logit ModelsAgnes Fussl, Sylvia Frühwirth-Schnatter, Rudolf Frühwirth. tomacs, 23(1):3, 2013. [doi]

2012

Generalized extreme value distribution with time-dependence using the AR and MA models in state space formJouchi Nakajima, Tsuyoshi Kunihama, Yasuhiro Omori, Sylvia Frühwirth-Schnatter. csda, 56(11):3241-3259, 2012. [doi]

2011

Panel data analysis: a survey on model-based clustering of time seriesSylvia Frühwirth-Schnatter. adac, 5(4):251-280, 2011. [doi]

2008

Bayesian parsimonious covariance estimation for hierarchical linear mixed modelsSylvia Frühwirth-Schnatter, Regina Tüchler. sac, 18(1):1-13, 2008. [doi]

Marginal likelihoods for non-Gaussian models using auxiliary mixture samplingSylvia Frühwirth-Schnatter, Helga Wagner. csda, 52(10):4608-4624, 2008. [doi]

Neural Network Models for Conditional Distribution Under Bayesian AnalysisTatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner. neco, 20(2):504-522, 2008. [doi]

2007

Auxiliary mixture sampling with applications to logistic modelsSylvia Frühwirth-Schnatter, Rudolf Frühwirth. csda, 51(7):3509-3528, 2007. [doi]

2006

Bayesian testing for non-linearity in volatility modelingTatiana Miazhynskaia, Sylvia Frühwirth-Schnatter, Georg Dorffner. csda, 51(3):2029-2042, 2006. [doi]

2002

Bayesian Estimation of the Heston Stochastic Volatility ModelSylvia Frühwirth-Schnatter, Leopold Sögner. or 2003: 480-485 [doi]

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