Cover Image

Wasserstein complexity penalization priors: a new class of penalizing complexity priors

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bolin, David, Simas, Alexandre B., Xiong, Zhen
Format:	Preprint
Published:	2023
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A parameterization of anisotropic Gaussian fields with penalized complexity priors
by: Llamazares-Elias, Liam, et al.
Published: (2024)

A new class of non-stationary Gaussian fields with general smoothness on metric graphs
by: Bolin, David, et al.
Published: (2025)

Bayesian shrinkage priors for penalized synthetic control estimators in the presence of spillovers
by: Fernández-Morales, Esteban, et al.
Published: (2025)

Penalizing complexity priors for Bayesian inference of circular models
by: Ye, Xiang, et al.
Published: (2025)

Log-Gaussian Cox Processes on General Metric Graphs
by: Bolin, David, et al.
Published: (2025)

Positive-definiteness in separable priors: effects on prior interpretability and inference
by: Carter, Jack Storror, et al.
Published: (2026)

A Unified and Computationally Efficient Non-Gaussian Statistical Modeling Framework
by: Bolin, David, et al.
Published: (2026)

A class of priors to perform asymmetric Bayesian wavelet shrinkage
by: Sousa, Alex Rodrigo dos Santos
Published: (2024)

Translating predictive distributions into informative priors
by: Manderson, Andrew A., et al.
Published: (2023)

Incorporating Correlated Nugget Effects in Multivariate Spatial Models: An Application to Argo Ocean Data
by: Saduakhas, Damilya, et al.
Published: (2025)

A flexible class of priors for orthonormal matrices with basis function-specific structure
by: North, Joshua S., et al.
Published: (2023)

Mixture priors for replication studies
by: Macrì-Demartino, Roberto, et al.
Published: (2024)

Logistic regression models: practical induced prior specification
by: Newman, Ken B., et al.
Published: (2025)

Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors
by: Zito, Alessandro, et al.
Published: (2023)

Infinitely divisible priors for multivariate survival functions
by: Brück, Florian
Published: (2025)

Wavelet shrinkage based on the raised cosine prior
by: Reina, Juliana Marchesi, et al.
Published: (2025)

Sparsifying transform priors in Gaussian graphical models
by: Gehrmann, Marcus, et al.
Published: (2026)

Meta-analytic-predictive priors based on a single study
by: Röver, Christian, et al.
Published: (2025)

Opaque prior distributions in Bayesian latent variable models
by: Merkle, Edgar C., et al.
Published: (2023)

A basket trial design based on power priors
by: Baumann, Lukas, et al.
Published: (2023)

Detecting and diagnosing prior and likelihood sensitivity with power-scaling
by: Kallioinen, Noa, et al.
Published: (2021)

On integral priors for multiple comparison in Bayesian model selection
by: Salmerón, Diego, et al.
Published: (2024)

An objective non-local prior for skew-symmetric models
by: Rubio, F. J.
Published: (2026)

Loss based prior for the degrees of freedom of the Wishart distribution
by: Rossini, Luca, et al.
Published: (2021)

Repulsive mixtures via the sparsity-inducing partition prior
by: Mozdzen, Alexander, et al.
Published: (2025)

Bayesian computation for high-dimensional Gaussian Graphical Models with spike-and-slab priors
by: Sulem, Deborah, et al.
Published: (2025)

On a wider class of prior distributions for graphical models
by: Natarajan, Abhinav, et al.
Published: (2022)

Bayesian design for mathematical models of fruit growth based on misspecified prior information
by: Najimuddin, Nushrath, et al.
Published: (2024)

Using prior information to boost power in correlation structure support recovery
by: Ding, Ziyang, et al.
Published: (2021)

Variance prior forms for high-dimensional Bayesian variable selection
by: Moran, Gemma E., et al.
Published: (2018)

On prior smoothing with discrete spatial data in the context of disease mapping
by: Retegui, Garazi, et al.
Published: (2025)

Bayesian non-linear subspace shrinkage using horseshoe priors
by: Duda, Julia Christin, et al.
Published: (2024)

Variational inference for approximate objective priors using neural networks
by: Baillie, Nils, et al.
Published: (2025)

Confidence sequences with informative, bounded-influence priors
by: Cortinovis, Stefano, et al.
Published: (2025)

Bayesian shrinkage priors subject to linear constraints
by: Ling, Zhi, et al.
Published: (2025)

Loss-based prior for tree topologies in BART models
by: Serafini, F., et al.
Published: (2024)

Bayesian inference on Cox regression models using catalytic prior distributions
by: Li, Weihao, et al.
Published: (2023)

A note on simulation methods for the Dirichlet-Laplace prior
by: Gruber, Luis, et al.
Published: (2025)

Gaussian process priors with Markov properties for effective reproduction number inference
by: Sebastian, Jessalyn N., et al.
Published: (2025)

The matryoshka doll prior: principled multiplicity correction in Bayesian model comparison
by: Womack, Andrew J, et al.
Published: (2015)