Imagen de Portada

BARTSIMP: flexible spatial covariate modeling and prediction using Bayesian additive regression trees

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Jiang, Alex Ziyu, Wakefield, Jon
Formato:	Preprint
Publicado:	2023
Materias:	Methodology Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A class of modular and flexible covariate-based covariance functions for nonstationary spatial modeling
por: Blasi, Federico, et al.
Publicado: (2024)

Convex estimation of Gaussian graphical regression models with covariates
por: Liu, Ruobin, et al.
Publicado: (2024)

flexBART: Flexible Bayesian regression trees with categorical predictors
por: Deshpande, Sameer K.
Publicado: (2022)

Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach
por: Cheng, Si, et al.
Publicado: (2023)

A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
por: Kim, Youngseok, et al.
Publicado: (2022)

Approximate Bayesian inference for cumulative probit regression models
por: Aliverti, Emanuele
Publicado: (2025)

Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regression
por: Zgodic, Anja, et al.
Publicado: (2023)

Augmented transfer regression learning for completely missing covariates
por: Zhao, Huali, et al.
Publicado: (2026)

Two-sample comparison through additive tree models for density ratios
por: Awaya, Naoki, et al.
Publicado: (2025)

Fast approximative estimation of conditional Shapley values when using a linear regression model or a polynomial regression model
por: Aanes, Fredrik Lohne
Publicado: (2025)

Accounting for shared covariates in semi-parametric Bayesian additive regression trees
por: Prado, Estevão B., et al.
Publicado: (2021)

Statistical ranking with dynamic covariates
por: Dong, Pinjun, et al.
Publicado: (2024)

Amortized Bayesian Local Interpolation NetworK: Fast covariance parameter estimation for Gaussian Processes
por: Feng, Brandon R., et al.
Publicado: (2024)

PliableBVS: A flexible Bayesian variable selection method for modeling interactions with mandatory modifying variables
por: Asenso, Theophilus Quachie, et al.
Publicado: (2026)

Guiding adaptive shrinkage by co-data to improve regression-based prediction and feature selection
por: van de Wiel, Mark A., et al.
Publicado: (2024)

A least distance estimator for a multivariate regression model using deep neural networks
por: Shin, Jungmin, et al.
Publicado: (2024)

Semi-supervised learning for linear extremile regression
por: Jiang, Rong, et al.
Publicado: (2025)

Deep classifier kriging for probabilistic spatial prediction of air quality index
por: Chen, Junyu, et al.
Publicado: (2025)

Improving the stability of the covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling
por: Wei, Jiani, et al.
Publicado: (2025)

Logistic regression models for patient-level prediction based on massive observational data: Do we need all data?
por: John, Luis H., et al.
Publicado: (2020)

Personalizing black-box models for nonparametric regression with minimax optimality
por: Li, Sai, et al.
Publicado: (2026)

A semi-supervised learning using over-parameterized regression
por: Hagiwara, Katsuyuki
Publicado: (2024)

A flexible Bayesian g-formula for causal survival analyses with time-dependent confounding
por: Chen, Xinyuan, et al.
Publicado: (2024)

Monte Carlo inference for semiparametric Bayesian regression
por: Kowal, Daniel R., et al.
Publicado: (2023)

Group selection and shrinkage: Structured sparsity for semiparametric additive models
por: Thompson, Ryan, et al.
Publicado: (2021)

Bayesian Federated Inference for regression models based on non-shared multicenter data sets from heterogeneous populations
por: Jonker, Marianne A, et al.
Publicado: (2024)

A flexible and interpretable spatial covariance model for data on graphs
por: Christensen, Michael F., et al.
Publicado: (2022)

Principal component analysis balancing prediction and approximation accuracy for spatial data
por: Cheng, Si, et al.
Publicado: (2024)

High-dimensional Bayesian Tobit regression for censored response with Horseshoe prior
por: Mai, The Tien
Publicado: (2025)

An interpretable neural network-based non-proportional odds model for ordinal regression
por: Okuno, Akifumi, et al.
Publicado: (2023)

Debiased high-dimensional regression calibration for errors-in-variables log-contrast models
por: Zhao, Huali, et al.
Publicado: (2024)

Design-marginal calibration of Gaussian process predictive distributions: Bayesian and conformal approaches
por: Pion, Aurélien, et al.
Publicado: (2025)

Asset price movement prediction using empirical mode decomposition and Gaussian mixture models
por: Palma, Gabriel R., et al.
Publicado: (2025)

Oblique Bayesian additive regression trees
por: Nguyen, Paul-Hieu V., et al.
Publicado: (2024)

Assessing the overall and partial causal well-specification of nonlinear additive noise models
por: Schultheiss, Christoph, et al.
Publicado: (2023)

Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling
por: Svensson, David, et al.
Publicado: (2025)

Network-based Neighborhood regression
por: Zhen, Yaoming, et al.
Publicado: (2024)

Progression: an extrapolation principle for regression
por: Buriticá, Gloria, et al.
Publicado: (2024)

Exact variance estimation for model-assisted survey estimators using U- and V-statistics
por: Dharamshi, Ameer, et al.
Publicado: (2025)

Conformal prediction for frequency-severity modeling
por: Graziadei, Helton, et al.
Publicado: (2023)