Posterior consistency for Bayesian inverse problems through stability and regression results
In the Bayesian approach, the a priori knowledge about the input of a mathematical model is described via a probability measure. The joint distribution of the unknown input and the data is then conditioned, using Bayes' formula, giving rise to the posterior distribution on the unknown input. In...
Egile nagusia: | Vollmer, S |
---|---|
Formatua: | Journal article |
Hizkuntza: | English |
Argitaratua: |
2013
|
Antzeko izenburuak
-
Automatic Tempered Posterior Distributions for Bayesian Inversion Problems
nork: Luca Martino, et al.
Argitaratua: (2021-04-01) -
Kernel Sliced Inverse Regression: Regularization and Consistency
nork: Qiang Wu, et al.
Argitaratua: (2013-01-01) -
Robust Bayesian Regression with Synthetic Posterior Distributions
nork: Shintaro Hashimoto, et al.
Argitaratua: (2020-06-01) -
Bayesian detection of causal rare variants under posterior consistency.
nork: Faming Liang, et al.
Argitaratua: (2013-01-01) -
Bayesian inverse problems and seismic inversion
nork: Lim, S
Argitaratua: (2016)