ArticleBiometrika2018
Scalar-on-Image Regression via the Soft-Thresholded Gaussian Process.
Article in Biometrika, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed.
- Interpretable Scalar-on-Image Linear Regression Models via the Generalized Dantzig Selector.Journal of the American Statistical Association · 2026Article
- A NOVEL BAYESIAN FRAMEWORK UNCOVERING BRAIN CONNECTIVITY-TO-SHAPE RELATIONSHIP IN PRECLINICAL ALZHEIMER'S DISEASE.The annals of applied statistics · 2026Article
- Bayesian Image Mediation Analysis.Journal of the American Statistical Association · 2026Article
- Bayesian thresholded modeling for integrating brain node and network predictors.Biostatistics (Oxford, England) · 2025Article
- Identification of Regions of Interest in Neuroimaging Data With Irregular Boundary Based on Semiparametric Transformation Models and Interval-Censored Outcomes.Statistics in medicine · 2025Article
- Bayesian Inference on Brain-Computer Interfaces via GLASS.Journal of the American Statistical Association · 2025Article
- Spatial Adaptive Selection using Binary Conditional Autoregressive Model with Application to Brain-Computer Interface.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2025Article
- Interpretable discriminant analysis for functional data supported on random nonlinear domains with an application to Alzheimer's disease.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2024Article
- A General Bayesian Functional Spatial Partitioning Method for Multiple Region Discovery Applied to Prostate Cancer MRI.Bayesian analysis · 2024Article
- Exploring heterogeneity and dynamics of meteorological influences on US PMSpatial statistics · 2024Article
- Robust High-Dimensional Regression with Coefficient Thresholding and its Application to Imaging Data Analysis.Journal of the American Statistical Association · 2024Article
- Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process.Journal of the American Statistical Association · 2024Article
- Simultaneous selection and inference for varying coefficients with zero regions: a soft-thresholding approach.Biometrics · 2023Article
- BAYESIAN INFERENCE AND DYNAMIC PREDICTION FOR MULTIVARIATE LONGITUDINAL AND SURVIVAL DATA.The annals of applied statistics · 2023Article
- Discussion of "LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures".Journal of the American Statistical Association · 2023Article
- SCALAR ON NETWORK REGRESSION VIA BOOSTING.The annals of applied statistics · 2022Article
- Prior Knowledge Guided Ultra-high Dimensional Variable Screening with Application to Neuroimaging Data.Statistica Sinica · 2022Article
- Article
- Bayesian Inferences on Neural Activity in EEG-Based Brain-Computer Interface.Journal of the American Statistical Association · 2022Article
- Bayesian inference and dynamic prediction of multivariate joint model with functional data: An application to Alzheimer's disease.Statistics in medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This work concerns spatial variable selection for scalar-on-image regression. We propose a new class of Bayesian nonparametric models and develop an efficient posterior computational aigorithm. The proposed soft-thresholded Gaussian process provides large prior support over the class of piecewise-smooth, sparse, and continuous spatially-varying regression coefficient functions. In addition, under some mild regularity conditions the soft-thresholded Gaussian proess prior leads to the posterior consistency for parameter estimation and variable selection for scalar-on-image regression, even when the number of predictors is larger than the sample size. The proposed method is compared to alternatives via simulation and applied to an electroen-cephalography study of alcoholism.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.