Results 81 to 90 of about 7,749,372 (301)

Bayesian hierarchical models combining different study types and adjusting for covariate imbalances: a simulation study to assess model performance.

PLoS ONE, 2011
BackgroundBayesian hierarchical models have been proposed to combine evidence from different types of study designs. However, when combining evidence from randomised and non-randomised controlled studies, imbalances in patient characteristics between ...
C Elizabeth McCarron, Eleanor M Pullenayegum, Lehana Thabane, Ron Goeree, Jean-Eric Tarride   +4 more
doaj   +1 more source

Estimation Parameters of Dependence Meta-Analytic Model: New Techniques for the Hierarchical Bayesian Model

Computation, 2022
Dependence in meta-analytic models can happen due to the same collected data or from the same researchers. The hierarchical Bayesian linear model in a meta-analysis that allows dependence in effect sizes is investigated in this paper.
Junaidi, Darfiana Nur, Irene Hudson, Elizabeth Stojanovski   +3 more
doaj   +1 more source

Bayesian Regularisation in Structured Additive Regression Models for Survival Data [PDF]

, 2008
During recent years, penalized likelihood approaches have attracted a lot of interest both in the area of semiparametric regression and for the regularization of high-dimensional regression models.
Konrath, Susanne, Kneib, Thomas, Fahrmeir, Ludwig   +2 more
core   +1 more source

Muscle Control of an Extra Robotic Digit

Advanced Robotics Research, EarlyView.
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ, Lucy Dowdall, Francesco Cenciarelli, Kitty Goodridge, Mabel Ziman, Hristo Dimitrov, Danielle Clode, Tamar R. Makin   +7 more
wiley   +1 more source

A Bayesian Hierarchical Cox Model with Elastic Net Regularization for Improved Survival Prediction and Feature Selection

Mathematics
In recent years, the growing availability of large-scale data across a wide range of disciplines has created new opportunities for developing models that improve the predictive accuracy of statistical models.
Bulus I. Doroh, Kazeem A. Dauda, Rasheed K. Lamidi   +2 more
doaj   +1 more source

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics [PDF]

, 2013
Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper,
Muhammad F Bari, Bari Muhammad F., Sirinukunwattana Korsuk, Bari, Muhammad F., Muhammad F. Bari, Savage, Richard S., David R. J. Snead, David R. J. Snead (475600), Richard S Savage, Richard S. Savage, Rajpoot Nasir M., Muhammad F. Bari (417733), Snead, David R. J., David R J Snead, Richard S. Savage (341629), Nasir M. Rajpoot, Korsuk Sirinukunwattana (475599), Rajpoot, Nasir M., Sirinukunwattana, Korsuk, Korsuk Sirinukunwattana, Snead, David R.J., Snead David R. J., Nasir M. Rajpoot (185555), Nasir M Rajpoot, Savage Richard S.   +24 more
core   +2 more sources

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source

Projecting malaria elimination in Thailand using Bayesian hierarchical spatiotemporal models

Scientific Reports, 2023
Thailand has set a goal of eliminating malaria by 2024 in its national strategic plan. In this study, we used the Thailand malaria surveillance database to develop hierarchical spatiotemporal models to analyze retrospective patterns and predict ...
Chawarat Rotejanaprasert, Saranath Lawpoolsri, Patiwat Sa-angchai, Amnat Khamsiriwatchara, Chantana Padungtod, Rungrawee Tipmontree, Lynette Menezes, Jetsumon Sattabongkot, Liwang Cui, Jaranit Kaewkungwal   +9 more
doaj   +1 more source

Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery [PDF]

, 2008
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linear combinations of pure component spectra contaminated by an additive ...
Chang, Chein-I, Tourneret, J.Y., Dobigeon, Nicolas, Tourneret, Jean-Yves, Chang, C.I., Dobigeon, N.   +5 more
core   +1 more source

Push the Limits: Human‐Like Multimodal Extreme Embodied Intelligence for Autonomous Racing

Advanced Robotics Research, EarlyView.
Autonomous racing tests embodied intelligence under extreme control limits of speed, actuation, and decision‐making. Inspired by human multimodality, we present Apex, an embodied agent deployed on a super‐formula racing car at Yas Marina. Integrating physics‐informed perception, multimodal learning, and tasking, Apex cuts lap times by 15% and achieves ...
Yanxin Zhou, Baichuan Lou, Wenhui Huang, Binbin Hu, Haohan Yang, Haochen Liu, Xiangkun He, Chee Kiong Ong, Yiran Zhang, Tianchu Su, Bolin Zhao, Xiaoyu Mo, Holden King Ho Li, Chen Lv   +13 more
wiley   +1 more source