Results 81 to 90 of about 2,889,354 (160)

Prenatal and childhood exposure to mixtures of endocrine-disrupting chemicals in association with measures of adiposity in childhood and adolescence

Environment International
Background: Childhood obesity is a global public health crisis. Endocrine-disrupting chemicals (EDCs) − widespread pollutants that interfere with hormonal and metabolic systems − may contribute to excessive adiposity.
Nuria Güil-Oumrait, Vishal Midya, Sandra India-Aldana, Augusto Anguita-Ruiz, Léa Maitre, Mariona Bustamante, Parisa Montazeri, Jose Urquiza, Line Småstuen Haug, Anne Lise Brantsæter, Barbara Heude, John Wright, Tiffany C. Yang, Rosemary R.C. McEachan, Euripides G. Stephanou, Regina Grazuleviciene, Rémy Slama, Leda Chatzi, Martine Vrijheid, Damaskini Valvi   +19 more
doaj   +1 more source

Bayesian Iterative Adaptive Lasso Quantile Regression

IOSR Journal of Mathematics, 2017
Rahim Alhamzawi, Haithem Taha Mohammad Ali   +1 more
openaire   +1 more source

Associations of exposure to volatile organic compounds with sleep health and potential mediators: analysis of NHANES data

Frontiers in Public Health
ObjectiveThe effect of environmental pollution on sleep has been widely studied, yet the relationship between exposure to volatile organic compounds (VOCs) and sleep health requires further exploration. We aimed to investigate the single and mixed effect
Yan Zhuang, Laifu Li, Yanqi Zhang, Fei Dai   +3 more
doaj   +1 more source

Bayesian adaptive Lasso quantile regression

Recently, variable selection by penalized likelihood has attracted much research interest. In this paper, we propose adaptive Lasso quantile regression (BALQR) from a Bayesian perspective.
R. ALHAMZAWI, D. F. BENOIT, K. YU
core  

Bayesian semiparametric additive quantile regression.

, 2013
Quantile regression provides a convenient framework for analyzing the impact of covariates on the complete conditional distribution of a response variable instead of only the mean.
Kneib, T., Waldmann, E., Flexeder, C., Yue, Y.R., Waldmann, Elisabeth, Lang, S., Kneib, Thomas, Lang, Stefan, Yue, Yu Ryan, Flexeder, Claudia   +9 more
core   +1 more source

Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components? [PDF]

This paper considers Bayesian regression with normal and doubleexponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that ...
De Mol, Christine, Reichlin, Lucrezia, Giannone, Domenico   +2 more
core   +2 more sources

Association among persistent chemical pollutants and infectious encephalitis: a mixture exposure and mediation approach

BMC Public Health
Background Most overlook the harmful effects on diseases, particularly the chronic neurotoxicity, which remains undetermined. This study aims to determine the impact of major environmental factors on infectious encephalitis.
Guolong Qu, Jianqiang Han, Zhenyao Song, Weiming Hou   +3 more
doaj   +1 more source

Additive models for quantile regression: model selection and confidence bandaids [PDF]

Additive models for conditional quantile functions provide an attractive framework for nonparametric regression applications focused on features of the response beyond its central tendency.
Roger Koenker
core  

L1-Penalized quantile regression in high-dimensional sparse models [PDF]

We consider median regression and, more generally, quantile regression in high-dimensional sparse models. In these models the overall number of regressors p is very large, possibly larger than the sample size n, but only s of these regressors have non ...
Victor Chernozhukov, Alexandre Belloni
core  

Post-l1-penalized estimators in high-dimensional linear regression models [PDF]

In this paper we study post-penalized estimators which apply ordinary, unpenalized linear regression to the model selected by first-step penalized estimators, typically LASSO. It is well known that LASSO can estimate the regression function at nearly the
Victor Chernozhukov, Alexandre Belloni
core