Skip to content
Descubridor Institucional UMAR
Inicio
Búsqueda avanzada
Explorar
Inicio
Búsqueda avanzada
Explorar
Login
Language
English
Deutsch
Español
Français
Italiano
All Fields
Title
Author
Subject
Call Number
ISBN/ISSN
Tag
Find
Advanced
Bayesian Model Selection via Composite Likelihood for High‐dimensional Data Integration
Bayesian Model Selection via Composite Likelihood for High‐dimensional Data Integration
Fuente:
Wiley Open Access
Saved in:
Bibliographic Details
Main Authors:
Guanlin Zhang
,
Yuehua Wu
,
Xin Gao
Format:
Artículo Open Access
Published:
Wiley
2024
Subjects:
Canadian Journal of Statistics
Online Access:
Acceder al recurso
Tags:
Add Tag
No Tags, Be the first to tag this record!
Cite this
Text this
Email this
Print
Export Record
Export to RefWorks
Export to EndNoteWeb
Export to EndNote
Save to List
Permanent link
Holdings
Description
Comments
Similar Items
Staff View
Description
DOI:
10.1002/cjs.11800
Similar Items
An SIR‐based Bayesian framework for COVID‐19 infection estimation
by: Haoyu Wu, et al.
Published: (2024)
Bayesian clustering of multivariate extremes
by: Sonia Alouini, et al.
Published: (2026)
Robust change point detection for high‐dimensional linear models with tolerance for outliers and heavy tails
by: Zhi Yang, et al.
Published: (2024)
A deep support vector clustering algorithm for unsupervised and semi‐supervised learning
by: Zhen Zhang, et al.
Published: (2025)
Bayesian jackknife empirical likelihood‐based inference for missing data and causal inference
by: Sixia Chen, et al.
Published: (2024)