Results 71 to 80 of about 5,004,642 (164)

Bayesian kernel machine meta-regression: an application in environmental epidemiology

Abstract In environmental epidemiology, the two-stage meta-analytic approach is widely used to analyze multi-location time-series data to investigate the health effects of environmental exposures. In the first stage, generalized linear models are fitted separately for each location to estimate the exposure-response association.
Jiseop Jeong, Daewon Yang, Whanhee Lee, Yejin Kim, Yeonseung Chung   +4 more
openaire   +1 more source

A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation. [PDF]

Multivariate kernel regression is an important tool for investigating the relationship between a response and a set of explanatory variables. It is generally accepted that the performance of a kernel regression estimator largely depends on the choice of ...
Robert D. Brooks, Maxwell L. King, Xibin Zhang   +2 more
core  

Regression depth and support vector machine [PDF]

The regression depth method (RDM) proposed by Rousseeuw and Hubert [RH99] plays an important role in the area of robust regression for a continuous response variable.
Christmann, Andreas
core  

Identification of nonlinear systems using generalized kernel models

, 2005
Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an
Wang, X. X., Harris, C. J., Wang, X.X., Hong, X., Harris, C.J., Chen, S.   +5 more
core   +1 more source

Gaussian Processes and Fast Matrix-Vector Multiplies [PDF]

, 2009
Gaussian processes (GPs) provide a flexible framework for probabilistic regression. The necessary computations involve standard matrix operations.
Murray, Iain, Murray, Iain; id_orcid
core  

Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data

BMC Bioinformatics, 2007
Background Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more important for our understanding of diseases at genomic level. Although many machine
Cheung Leo, Zhao Xin
doaj   +1 more source

Assessing the Risk of Heart Attack: A Bayesian Kernel Machine Regression Analysis of Heavy Metal Mixtures

Abstract Background: The assessment of heavy metals' effects on human health is frequently limited to investigating one metal or a group of related metals. The effect of heavy metals mixture on heart attack is unknown. Methods: This study applied the Bayesian kernel machine regression model (BKMR) to the 2011-2016 National Health and Nutrition ...
Ibrahimou, Boubakari, Hasan, Kazi Tanvir, Burchfield, Shelbie, Salihu, Hamisu, Zhu, Yiliang, Dagne, Getachew, De La Rosa, Mario, Melesse, Assefa, Lucchini, Roberto, Bursac, Zoran   +9 more
openaire   +2 more sources

Associations of metal mixtures with insulin resistance and glucose homeostasis in U.S. adults from the NHANES 2011–2018

Scientific Reports
Research on the association of metal mixtures with glucose-insulin homeostasis is limited, and previous studies have typically focused on single metals. This study utilized data from 3110 adult subjects in the NHANES survey (2011–2018).
Qinting Wu, Ruijing Gan, Siying Chen, Mocan Qiu, Jing Chen, Daizheng Huang   +5 more
doaj   +1 more source

Impact of toxic metal exposure on blood pressure: Insights into individual and combined effects with Bayesian kernel machine regression

Ecotoxicology and Environmental Safety
Hypertension is a leading global health issue, influenced by environmental factors such as metal exposure. Metals elements like arsenic (As), cadmium (Cd), chromium (Cr), mercury (Hg), lead (Pb), and nickel (Ni) can disrupt blood pressure regulation through oxidative stress and endothelial dysfunction.
Ren, Rui, Yang, Zhongfang, Du, Shaoxi, Zhi, Qian, He, Aoyue, Zhang, Rongqiang   +5 more
openaire   +2 more sources

Exposure to hair metals and metal-mixtures associated with blood lipids and dyslipidemia in Chinese adults: Evidence from a national cross-sectional study

Ecotoxicology and Environmental Safety
Background: Emerging evidence suggests that exposure to metals is associated with dyslipidemia; however, very little data is available on metal exposure in hair, and data regarding their joint and interactive effects for different metals on dyslipidemia ...
Yunjiang Yu, Wenjie Meng, Xiaohui Zhu, Zongrui Li, Tong Zheng, Ping He, Ying Yu, Chenyin Dong, Zhenchi Li, Hongxuan Kuang, Mingdeng Xiang, Xiaodi Qin, Yang Zhou   +12 more
doaj   +1 more source