Sylvia Frühwirth-Schnatter

Sylvia Frühwirth-Schnatter (born 21 May 1959) is an Austrian statistician and professor of applied statistics and econometrics at the Vienna University of Economics and Business. She is known for her research in Bayesian analysis. In 2020 she was the President of the International Society for Bayesian Analysis. Provided by Wikipedia
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  1. 1
    Das Unbeobachtbare erfassen - Dynamische stochastische Modelle in den Umweltwissenschaften
    by Frühwirth-Schnatter, Sylvia
    Published 1991
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  2. 2
    Applied State Space Modelling of Non-Gaussian Time Series using Integration-based Kalman-filtering
    by Frühwirth-Schnatter, Sylvia
    Published 1993
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  3. 3
    Recursive Residuals and Model Diagnostics for Normal and Non-Normal State Space Models
    by Frühwirth-Schnatter, Sylvia
    Published 1994
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  4. 4
    Fully Bayesian Analysis of Switching Gaussian State Space Models
    by Frühwirth-Schnatter, Sylvia
    Published 2000
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  5. 5
    On Fuzzy Bayesian Inference
    by Frühwirth-Schnatter, Sylvia
    Published 1990
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  6. 6
    Monitoring von ökologischen und biometrischen Prozessen mit statistischen Filtern
    by Frühwirth-Schnatter, Sylvia
    Published 1991
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  7. 7
    MCMC Estimation of Classical and Dynamic Switching and Mixture Models
    by Frühwirth-Schnatter, Sylvia
    Published 1998
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  8. 8
    Bayesian Model Discrimination and Bayes Factors for Normal Linear State Space Models
    by Frühwirth-Schnatter, Sylvia
    Published 1993
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  9. 9
    Model Likelihoods and Bayes Factors for Switching and Mixture Models
    by Frühwirth-Schnatter, Sylvia
    Published 2002
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  10. 10
    Model Likelihoods and Bayes Factors for Switching and Mixture Models
    by Frühwirth-Schnatter, Sylvia
    Published 2000
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  11. 11
    Data Augmentation and Dynamic Linear Models
    by Frühwirth-Schnatter, Sylvia
    Published 1992
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  12. 12
    Conjoint Analysis Using Mixed Effect Models
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  13. 13
    Bayesian Analysis of Switching ARCH Models
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  14. 14
    Bayesian parsimonious covariance estimation for hierarchical linear mixed models
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  15. 15
    A comparison of Bayesian model selection based on MCMC with an application to GARCH-type models
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  16. 16
    The Heterogeneity Model and its Special Cases. An Illustrative Comparison.
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  17. 17
    Bayesian latent class metric conjoint analysis. A case study from the Austrian mineral water market.
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  18. 18
    Bayesian analysis of the heterogeneity model
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  19. 19
    A Fully Bayesian Analysis of Multivariate Latent Class Models with an Application to Metric Conjoint Analysis
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  20. 20
    Fully Bayesian Analysis of Multivariate Latent Class Models with an Application to Metric Conjoint Analysis
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