Results 31 to 40 of about 1,354,633 (198)

A systematic comparison of statistical methods to detect interactions in exposome-health associations

Environmental Health, 2017
Background There is growing interest in examining the simultaneous effects of multiple exposures and, more generally, the effects of mixtures of exposures, as part of the exposome concept (being defined as the totality of human environmental exposures ...
Jose Barrera-Gómez, Lydiane Agier, Lützen Portengen, Marc Chadeau-Hyam, Lise Giorgis-Allemand, Valérie Siroux, Oliver Robinson, Jelle Vlaanderen, Juan R. González, Mark Nieuwenhuijsen, Paolo Vineis, Martine Vrijheid, Roel Vermeulen, Rémy Slama, Xavier Basagaña   +14 more
doaj   +1 more source

Fault Relevant Variable Selection for Fault Diagnosis

IEEE Access, 2020
In process monitoring, fault relevant variable selection and fault diagnosis are two important branches. But they are often discussed independently and scarcely integrated in research.
Ruixiang Deng, Zhenbang Wang, Yunpeng Fan   +2 more
doaj   +1 more source

Multidimensional Population Health Modeling: A Data-Driven Multivariate Statistical Learning Approach

IEEE Access, 2022
Population health is multidimensional in nature, having complex relationships with the various health determinants. However, most previous studies investigate a single dimension of population health using linear models, failing to capture the ...
Zhiyuan Wei, Adil Baran Narin, Sayanti Mukherjee   +2 more
doaj   +1 more source

Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications [PDF]

, 2010
Food authenticity studies are concerned with determining if food samples have been correctly labelled or not. Discriminant analysis methods are an integral part of the methodology for food authentication.
Nema Dean, Dean, Nema, Murphy, T.B., Raftery, A.E., Murphy, Thomas Brendan, Thomas Brendan Murphy, Raftery, Adrian E., Adrian E. Raftery, Dean, N.   +8 more
core   +1 more source

Binary and Ordinal Random Effects Models Including Variable Selection [PDF]

, 2010
A likelihood-based boosting approach for fitting binary and ordinal mixed models is presented. In contrast to common procedures it can be used in high-dimensional settings where a large number of potentially influential explanatory variables is available.
Groll, Andreas, Tutz, Gerhard
core   +1 more source

Reinforced variable selection

Statistical Theory and Related Fields
Variable selection identifies the best subset of covariates when building the prediction model, among all possible subsets. In this paper, we propose a novel reinforced variable selection method, called ‘Actor-Critic-Predictor’. The actor takes an action
Yuan Le, Yang Bai, Fan Zhou
doaj   +1 more source

VARIABLE SELECTION BY SUBSAMPLING RANKING FORWARD SELECTION (SURF)

, 2023
Traditional statistical methods face lots of challenges in model fitting, variable selection, and model diagnosis when analysing high-dimensional data.
LIU, LIHUI
core  

Statistical Sources of Variable Selection Bias in Classification Tree Algorithms Based on the Gini Index [PDF]

, 2005
Evidence for variable selection bias in classification tree algorithms based on the Gini Index is reviewed from the literature and embedded into a broader explanatory scheme: Variable selection bias in classification tree algorithms based on the Gini ...
Strobl, Carolin
core   +1 more source

Feature Selection based on the Local Lift Dependence Scale

Entropy, 2018
This paper uses a classical approach to feature selection: minimization of a cost function applied on estimated joint distributions. However, in this new formulation, the optimization search space is extended.
Diego Marcondes, Adilson Simonis, Junior Barrera   +2 more
doaj   +1 more source

Analysis of Information-Based Nonparametric Variable Selection Criteria

Entropy, 2020
We consider a nonparametric Generative Tree Model and discuss a problem of selecting active predictors for the response in such scenario. We investigated two popular information-based selection criteria: Conditional Infomax Feature Extraction (CIFE) and ...
Małgorzata Łazęcka, Jan Mielniczuk
doaj   +1 more source