Bayesian Analysis of Sigmoidal Gaussian Cox Processes via Data Augmentation
Fuente:
arXiv
Guardado en:
| Autores principales: | Alie, Renaud, Stephens, David A., Schmidt, Alexandra M. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Computational Considerations for the Linear Model of Coregionalization
por: Alie, Renaud, et al.
Publicado: (2024)
por: Alie, Renaud, et al.
Publicado: (2024)
Log-Gaussian Cox Processes on General Metric Graphs
por: Bolin, David, et al.
Publicado: (2025)
por: Bolin, David, et al.
Publicado: (2025)
Exact Bayesian Gaussian Cox Processes Using Random Integral
por: Tang, Bingjing, et al.
Publicado: (2024)
por: Tang, Bingjing, et al.
Publicado: (2024)
Inference for Log-Gaussian Cox Point Processes using Bayesian Deep Learning: Application to Human Oral Microbiome Image Data
por: Wang, Shuwan, et al.
Publicado: (2025)
por: Wang, Shuwan, et al.
Publicado: (2025)
Correlated Bayesian Additive Regression Trees with Gaussian Process for Regression Analysis of Dependent Data
por: a, Xuetao Lu, et al.
Publicado: (2023)
por: a, Xuetao Lu, et al.
Publicado: (2023)
Bayesian variable selection in a Cox proportional hazards model with the "Sum of Single Effects" prior
por: Yang, Yunqi, et al.
Publicado: (2025)
por: Yang, Yunqi, et al.
Publicado: (2025)
What Influences the Field Goal Attempts of Professional Players? Analysis of Basketball Shot Charts via Log Gaussian Cox Processes with Spatially Varying Coefficients
por: Cao, Jiahao, et al.
Publicado: (2025)
por: Cao, Jiahao, et al.
Publicado: (2025)
Efficient Bayesian Inference in the Cox Model via Rank-Ordered Likelihood
por: Ohigashi, Tomohiro, et al.
Publicado: (2026)
por: Ohigashi, Tomohiro, et al.
Publicado: (2026)
Semi-parametric Bayesian inference under Neyman orthogonality
por: Sabbagh, Magid, et al.
Publicado: (2026)
por: Sabbagh, Magid, et al.
Publicado: (2026)
Posterior Uncertainty for Targeted Parameters in Bayesian Bootstrap Procedures
por: Sabbagh, Magid, et al.
Publicado: (2026)
por: Sabbagh, Magid, et al.
Publicado: (2026)
Bayesian Bridge Gaussian Process Regression
por: Xu, Minshen, et al.
Publicado: (2025)
por: Xu, Minshen, et al.
Publicado: (2025)
Non-parametric Bayesian inference via loss functions under model misspecification
por: Luo, Yu, et al.
Publicado: (2021)
por: Luo, Yu, et al.
Publicado: (2021)
Bayesian Inference of Spatially Varying Correlations via the Thresholded Correlation Gaussian Process
por: Li, Moyan, et al.
Publicado: (2024)
por: Li, Moyan, et al.
Publicado: (2024)
Bayesian Variable Selection via Hierarchical Gaussian Process Model in Computer Experiments
por: Yao, Xiao, et al.
Publicado: (2024)
por: Yao, Xiao, et al.
Publicado: (2024)
Two-sample Bayesian Nonparametric Hypothesis Testing
por: Holmes, Chris C., et al.
Publicado: (2009)
por: Holmes, Chris C., et al.
Publicado: (2009)
Bayesian inference on Cox regression models using catalytic prior distributions
por: Li, Weihao, et al.
Publicado: (2023)
por: Li, Weihao, et al.
Publicado: (2023)
Nonparametric Bayesian Adjustment of Unmeasured Confounders in Cox Proportional Hazards Models
por: Orihara, Shunichiro, et al.
Publicado: (2023)
por: Orihara, Shunichiro, et al.
Publicado: (2023)
Bayesian regularization for flexible baseline hazard functions in Cox survival models
por: Lázaro, Elena, et al.
Publicado: (2024)
por: Lázaro, Elena, et al.
Publicado: (2024)
Bayesian Inference for Non-Gaussian Simultaneous Autoregressive Models with Missing Data
por: Wijayawardhana, Anjana, et al.
Publicado: (2025)
por: Wijayawardhana, Anjana, et al.
Publicado: (2025)
Bayesian Inference for Stationary Points in Gaussian Process Regression Models for Event-Related Potentials Analysis
por: Yu, Cheng-Han, et al.
Publicado: (2020)
por: Yu, Cheng-Han, et al.
Publicado: (2020)
The Cox-Polya-Gamma Algorithm for Flexible Bayesian Inference of Multilevel Survival Models
por: Ren, Benny, et al.
Publicado: (2024)
por: Ren, Benny, et al.
Publicado: (2024)
The Bayesian Gaussian Process Latent Variable Model for Spatio-Temporal Stream Networks
por: Basson, Marno, et al.
Publicado: (2026)
por: Basson, Marno, et al.
Publicado: (2026)
Testing Normality of Data Transformed by Maximum Likelihood Box Cox
por: Hawkins, Douglas M
Publicado: (2024)
por: Hawkins, Douglas M
Publicado: (2024)
Semi-Implicit Approaches for Large-Scale Bayesian Spatial Interpolation
por: Garneau, Sébastien, et al.
Publicado: (2025)
por: Garneau, Sébastien, et al.
Publicado: (2025)
Cox Regression on the Plane
por: Travis-Lumer, Yael, et al.
Publicado: (2025)
por: Travis-Lumer, Yael, et al.
Publicado: (2025)
Bayesian Image-on-Image Regression via Deep Kernel Learning based Gaussian Processes
por: Ma, Guoxuan, et al.
Publicado: (2023)
por: Ma, Guoxuan, et al.
Publicado: (2023)
Robust and Data-Adaptive Integration of Nonconcurrent Data in Platform Trials via Gaussian Processes
por: Qian, Yuhan, et al.
Publicado: (2026)
por: Qian, Yuhan, et al.
Publicado: (2026)
A Bayesian Take on Gaussian Process Networks
por: Giudice, Enrico, et al.
Publicado: (2023)
por: Giudice, Enrico, et al.
Publicado: (2023)
Bayesian Causal Inference with Gaussian Process Networks
por: Giudice, Enrico, et al.
Publicado: (2024)
por: Giudice, Enrico, et al.
Publicado: (2024)
Quantile Forecast Matching with a Bayesian Quantile Gaussian Process Model
por: Wadsworth, Spencer, et al.
Publicado: (2025)
por: Wadsworth, Spencer, et al.
Publicado: (2025)
Post-Selection Inference for the Cox Model with Interval-Censored Data
por: Zhang, Jianrui, et al.
Publicado: (2023)
por: Zhang, Jianrui, et al.
Publicado: (2023)
On the PM2.5 -- Mortality Association: A Bayesian Model for Spatio-Temporal Confounding
por: Zaccardi, Carlo, et al.
Publicado: (2024)
por: Zaccardi, Carlo, et al.
Publicado: (2024)
Bayesian Levy-Dynamic Spatio-Temporal Process: Towards Big Data Analysis
por: Bhattacharya, Sourabh
Publicado: (2021)
por: Bhattacharya, Sourabh
Publicado: (2021)
A Bayesian hierarchical model for disease mapping that accounts for scaling and heavy-tailed latent effects
por: Michal, Victoire, et al.
Publicado: (2021)
por: Michal, Victoire, et al.
Publicado: (2021)
Locally weighted minimum contrast estimation for spatio-temporal log-Gaussian Cox processes
por: D'Angelo, Nicoletta, et al.
Publicado: (2022)
por: D'Angelo, Nicoletta, et al.
Publicado: (2022)
Empirical Bayes Shrinkage and False Discovery Rate Estimation, Allowing For Unwanted Variation
por: Gerard, David, et al.
Publicado: (2017)
por: Gerard, David, et al.
Publicado: (2017)
Efficient Gibbs Sampling in Cox Regression Models Using Composite Partial Likelihood and Pólya-Gamma Augmentation
por: Tamano, Shu, et al.
Publicado: (2025)
por: Tamano, Shu, et al.
Publicado: (2025)
Temporal network analysis via a degree-corrected Cox model
por: Chen, Yuguo, et al.
Publicado: (2025)
por: Chen, Yuguo, et al.
Publicado: (2025)
Modal Analysis of Spatiotemporal Data via Multivariate Gaussian Process Regression
por: Song, Jiwoo, et al.
Publicado: (2024)
por: Song, Jiwoo, et al.
Publicado: (2024)
Mastering Rare Event Analysis: Optimal Subsample Size in Logistic and Cox Regressions
por: Agassi, Tal, et al.
Publicado: (2024)
por: Agassi, Tal, et al.
Publicado: (2024)
Ejemplares similares
-
Computational Considerations for the Linear Model of Coregionalization
por: Alie, Renaud, et al.
Publicado: (2024) -
Log-Gaussian Cox Processes on General Metric Graphs
por: Bolin, David, et al.
Publicado: (2025) -
Exact Bayesian Gaussian Cox Processes Using Random Integral
por: Tang, Bingjing, et al.
Publicado: (2024) -
Inference for Log-Gaussian Cox Point Processes using Bayesian Deep Learning: Application to Human Oral Microbiome Image Data
por: Wang, Shuwan, et al.
Publicado: (2025) -
Correlated Bayesian Additive Regression Trees with Gaussian Process for Regression Analysis of Dependent Data
por: a, Xuetao Lu, et al.
Publicado: (2023)