Fully Bayesian Analysis of Switching Gaussian State Space Models
By Sylvia Frühwirth-Schnatter. 2001
50 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/a6d0367d5b9f04a37dd9a2f2512e0a34c09fa2df
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Thomas Otter
- Regina Tüchler
- Helga Wagner
- Sylvia Frühwirth-Schnatter
- S. Kaufmann
- Anna Pajor
- Jeroen K. Vermunt
- Gregor Kastner
In Statistics and Probability
- Thomas Otter
- Regina Tüchler
- Helga Wagner
- Sylvia Frühwirth-Schnatter
- S. Kaufmann
- Anna Pajor
- Jeroen K. Vermunt
- Kerrie L. Mengersen
Citations in the corpus
- Stochastic model specification search for Gaussian and partial non-Gaussian state space models (2010, methodology): “This is in line with Gelman (2006) who came to similar conclusions for the related random-effects model.”
- Bayesian Analysis of the Heterogeneity Model (2004, methodology): “One may apply the idea of Frühwirth-Schnatter (2001a) to explore simulations from the unconstrained posterior in order to find an identifiability constraintR which is able to separate the posterior modes and by this to identify simulations from one labeling subspace, say L .”