Works (6)
Updated: July 5th, 2023 15:36
2021 journal article
Posterior contraction in sparse generalized linear models
BIOMETRIKA, 108(2), 367–379.
author keywords: Fractional posterior; Generalized linear model; High-dimensional regression; Posterior contraction rate; Sparsity-inducing prior
TL;DR:
This work studies posterior contraction rates in sparse high-dimensional generalized linear models using priors incorporating sparsity, and shows that Bayesian methods achieve convergence properties analogous to lasso-type procedures.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Source: Web Of Science
Added: July 12, 2021
2021 journal article
Unified Bayesian theory of sparse linear regression with nuisance parameters
ELECTRONIC JOURNAL OF STATISTICS, 15(1), 3040–3111.
author keywords: Bernstein-von Mises theorems; High-dimensional regression; Model selection consistency; Posterior contraction rates; Sparse priors
projecteuclid.org (publisher PDF)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Source: Web Of Science
Added: June 28, 2021
2020 journal article
Bayesian linear regression for multivariate responses under group sparsity
BERNOULLI, 26(3), 2353–2382.
author keywords: Bayesian variable selection; covariance matrix; group sparsity; multivariate linear regression; posterior contraction rate; Renyi divergence; spike-and-slab prior
TL;DR:
The posterior contraction rate is derived using the general theory by constructing a suitable test from the first principle using moment bounds for certain likelihood ratios, which leads to posterior concentration around the truth with respect to the average Renyi divergence of order 1/2.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Source: Web Of Science
Added: May 18, 2020
2019 journal article
Emerging procurement technology: data analytics and cognitive analytics
INTERNATIONAL JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT, 49(10), 972–1002.
Contributors: R. Handfield n , * & T. Choi *
TL;DR:
The procurement analytics landscape developed in this research suggests that the authors will continue to see major shifts in the sourcing and supply chain technology environment in the next five years and detailed implementation strategies of emerging procurement technologies are suggested, contributing to the existing body of the literature and industry reports.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure
(Web of Science)
Sources: Web Of Science, ORCID
Added: December 16, 2019
2018 journal article
Analysis of Poisson varying-coefficient models with autoregression
Statistics, 52(1), 34–49.
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
16. Peace, Justice and Strong Institutions
(OpenAlex)
Source: NC State University Libraries
Added: August 6, 2018
2017 journal article
Analysis of binary longitudinal data with time-varying effects
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 112, 145–153.
author keywords: Longitudinal data; Probit mixed model; Nonparametric regression; Partial collapse; Repeated measures
TL;DR:
A Bayesian method is proposed for the analysis of binary longitudinal data with time-varying regression coefficients and random effects to account for nonlinear subject-specific effects over time as well as between-subject variation.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
10. Reduced Inequalities
(OpenAlex)
Source: Web Of Science
Added: August 6, 2018
Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.
Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
