Cover Image

Bayesian Design of Experiments in the Presence of Nuisance Parameters

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Golchi, Shirin, Hagar, Luke
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Design of Bayesian Clinical Trials with Clustered Data
by: Hagar, Luke, et al.
Published: (2025)

An Efficient Approach to Design Bayesian Platform Trials
by: Hagar, Luke, et al.
Published: (2025)

Group Sequential Design with Posterior and Posterior Predictive Probabilities
by: Hagar, Luke, et al.
Published: (2025)

Bayesian Design and Analysis of Precision Trials with Partial Borrowing
by: Golchi, Shirin, et al.
Published: (2026)

Estimating the Sampling Distribution of Posterior Decision Summaries in Bayesian Clinical Trials
by: Golchi, Shirin, et al.
Published: (2023)

Design of Bayesian A/B Tests Controlling False Discovery Rates and Power
by: Hagar, Luke, et al.
Published: (2023)

Bayesian Optimization for Identification of Optimal Biological Dose Combinations in Personalized Dose-Finding Trials
by: Willard, James, et al.
Published: (2024)

Economical Experimental Design with Generalized Posteriors
by: Hagar, Luke, et al.
Published: (2026)

Sparse two-stage Bayesian meta-analysis for individualized treatments
by: Shen, Junwei, et al.
Published: (2024)

A Bayesian adaptive enrichment design using aggregate historical data to inform individualized treatment recommendations
by: Maleyeff, Lara, et al.
Published: (2026)

fkbma: An R Package for Detecting Tailoring Variables with Free-Knot B-Splines and Bayesian Model Averaging
by: Maleyeff, Lara, et al.
Published: (2025)

Bioequivalence Design with Sampling Distribution Segments
by: Hagar, Luke, et al.
Published: (2023)

An Economical Approach to Design with Precision Criteria
by: Hagar, Luke, et al.
Published: (2023)

An Economical Approach to Design Posterior Analyses
by: Hagar, Luke, et al.
Published: (2024)

Identifying Treatment Effect Heterogeneity with Bayesian Hierarchical Adjustable Random Partition in Adaptive Enrichment Trials
by: Zhao, Xianglin, et al.
Published: (2025)

An adaptive enrichment design using Bayesian model averaging for selection and threshold-identification of tailoring variables
by: Maleyeff, Lara, et al.
Published: (2024)

Bayesian Optimization for Personalized Dose-Finding Trials with Combination Therapies
by: Willard, James, et al.
Published: (2023)

Posterior Ramifications of Prior Dependence Structures
by: Hagar, Luke, et al.
Published: (2023)

Fast Power Curve Approximation for Posterior Analyses
by: Hagar, Luke, et al.
Published: (2023)

Testing Inequalities Linear in Nuisance Parameters
by: Cox, Gregory Fletcher, et al.
Published: (2025)

Unified Inference on Moment Restrictions with Nuisance Parameters
by: Li, Xingyu, et al.
Published: (2022)

An Efficient Framework for Robust Sample Size Determination
by: Hagar, Luke, et al.
Published: (2025)

The Influence of Nuisance Parameter Uncertainty on Statistical Inference in Practical Data Science Models
by: Wan, Yunrong
Published: (2024)

Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameters
by: Bhattacharya, Sohom, et al.
Published: (2025)

Collaborative Design of Controlled Experiments in the Presence of Subject Covariates
by: Fisher, William, et al.
Published: (2024)

GMM with Many Weak Moment Conditions and Nuisance Parameters: General Theory and Applications to Causal Inference
by: Wang, Rui, et al.
Published: (2025)

Bayesian Active Learning in the Presence of Nuisance Parameters
by: Sloman, Sabina J., et al.
Published: (2023)

Optimal Stopping for Sequential Bayesian Experimental Design
by: Cheng, Chen, et al.
Published: (2025)

Robust Design in the Presence of Aleatoric and Epistemic Uncertainty
by: Crespo, Luis G.
Published: (2026)

fdesigns: Bayesian Optimal Designs of Experiments for Functional Models in R
by: Michaelides, Damianos, et al.
Published: (2024)

A Bayesian Generalized Bridge Regression Approach to Covariance Estimation in the Presence of Covariates
by: Zhao, Christina, et al.
Published: (2024)

Identifying Causal Effects using Instrumental Time Series: Nuisance IV and Correcting for the Past
by: Thams, Nikolaj, et al.
Published: (2022)

Constructing Bayesian Optimal Designs for Discrete Choice Experiments by Simulated Annealing
by: Mao, Yicheng, et al.
Published: (2024)

Stable Transport Meta-Analysis for Heterogeneous Cardiovascular Trials: A Nuisance-Anchor Framework with a Sign-Stability Diagnostic
by: Tanboga, Ibrahim Halil
Published: (2026)

Recursive Nested Filtering for Efficient Amortized Bayesian Experimental Design
by: Iqbal, Sahel, et al.
Published: (2024)

Maximin Robust Bayesian Experimental Design
by: Abdulsamad, Hany, et al.
Published: (2026)

Unbiased Parameter Estimation for Bayesian Inverse Problems
by: Chada, Neil K., et al.
Published: (2025)

Estimating the Sampling Distribution of Posterior Decision Summaries in Bayesian Clinical Trials
by: Shirin Golchi, et al.
Published: (2024)

Batch-based Bayesian Optimal Experimental Design in Linear Inverse Problems
by: Mäkinen, Sofia, et al.
Published: (2026)

Deep Optimal Experimental Design for Parameter Estimation Problems
by: Siddiqui, Md Shahriar Rahim, et al.
Published: (2024)