Results 31 to 40 of about 1,681,604 (218)

Sparse Bayesian Learning Using Adaptive LASSO Priors

, 2022
To improve the recovery accuracy of sparse signal, we study on sparse Bayesian learning (SBL) algorithm using adaptive least absolute shrinkage and selection operator (LASSO) priors.
Bai, Zong Long, Shi, Li Ming, Sun, Jin Wei   +2 more
core   +1 more source

Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors [PDF]

Statistics and Its Interface, 2013
Metabolic processes are essential for cellular function and survival. We are interested in inferring a metabolic network in activated microglia, a major neuroimmune cell in the brain responsible for the neuroinflammation associated with neurological diseases, based on a set of quantified metabolites.
Peterson, Christine, Vannucci, Marina, Karakas, Cemal, Choi, William, Ma, Lihua, Maletic-Savatic, Mirjana   +5 more
openaire   +3 more sources

A Fast Algorithm For The Bayesian Adaptive Lasso

, 2012
Publication in the conference proceedings of EUSIPCO, Bucharest, Romania ...
Athanasios A. Rontogiannis, Konstantinos E. Themelis, Konstantinos Koutroumbas   +2 more
openaire   +3 more sources

Who Knows Best What the Next Year Will Hold for You? The Validity of Direct and Personality‐based Predictions of Future Life Experiences Across Different Perceivers

European Journal of Personality, EarlyView., 2020
Abstract This study explored the validity of person judgements by targets and their acquaintances (‘informants’) in longitudinally predicting a broad range of psychologically meaningful life experiences. Judgements were gathered from four sources (targets, N = 189; and three types of informants, N = 1352), and their relative predictive validity was ...
Nele M. Wessels, Johannes Zimmermann, Daniel Leising, Jan‐Erik Lönnqvist   +3 more
wiley   +1 more source

Locally Adaptive Bayesian P-Splines with a Normal-Exponential-Gamma Prior [PDF]

, 2008
The necessity to replace smoothing approaches with a global amount of smoothing arises in a variety of situations such as effects with highly varying curvature or effects with discontinuities.
Scheipl, Fabian, Kneib, Thomas
core   +1 more source

Bayesian Adaptive Lasso binary regression with ridge parameter

Journal of Physics: Conference Series, 2019
Abstract The variable selection (VS) characteristic was considered very important in the data analysis. Regularization technique is one gorgeous way that has proven effective for dealing with high dimensional data. In previous years, statistical researchers have made great efforts in developing procedures of regularization to solved ...
Haider Kadhim Abbas Hilali, Rahim Alhamzawi   +1 more
openaire   +1 more source

Inference of gene regulatory networks from genetic perturbations with linear regression model. [PDF]

PLoS ONE, 2013
It is an effective strategy to use both genetic perturbation data and gene expression data to infer regulatory networks that aims to improve the detection accuracy of the regulatory relationships among genes.
Zijian Dong, Tiecheng Song, Chuang Yuan
doaj   +1 more source

Associations of multiple plasma metals with the risk of metabolic syndrome: A cross-sectional study in the mid-aged and older population of China

Ecotoxicology and Environmental Safety, 2022
Background: Metal exposures have been reported to be related to the progress of metabolic syndrome (MetS), however, the currents results were still controversial, and the evidence about the effect of multi-metal exposure on MetS were limited.
Suli Huang, Danrong Zhong, Ziquan Lv, Jinquan Cheng, Xuan Zou, Tian Wang, Ying Wen, Chao Wang, Shuyuan Yu, Hui Huang, Lu Li, Zhiqiang Nie   +11 more
doaj   +1 more source

A Functional Model for Structure Learning and Parameter Estimation in Continuous Time Bayesian Network: An Application in Identifying Patterns of Multiple Chronic Conditions

IEEE Access, 2021
Bayesian networks are powerful statistical models to study the probabilistic relationships among sets of random variables with significant applications in disease modeling and prediction.
Syed Hasib Akhter Faruqui, Adel Alaeddini, Jing Wang, Carlos A. Jaramillo, Mary Jo Pugh   +4 more
doaj   +1 more source

A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi, Giorgio Ricciardiello Mejia, Andre Metzger, Kang Hyun Ryu, Salonee Marwaha, Eva Grzegorczyk, Li Zhou, Eliana Jacobs, Boris Gilyadov, Claudia Kunney, Liqhwa Ncube, Ankit Parekh, Emmanuel Mignot, Fanny M. Elahi, Joseph Winer, Kathleen Poston, Andreas Brink‐Kjaer, Emmanuel H. During   +17 more
wiley   +1 more source