Results 11 to 20 of about 1,312,626 (282)
New adaptive lasso approaches for variable selection in automated pharmacovigilance signal detection [PDF]
BMC Medical Research Methodology, 2021 Background Adverse effects of drugs are often identified after market introduction. Post-marketing pharmacovigilance aims to detect them as early as possible and relies on spontaneous reporting systems collecting suspicious cases.
Émeline Courtois +2 more
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Construction of an anthropometric discriminant model for identification of elite swimmers: an adaptive lasso approach [PDF]
PeerJ, 2023 Background Anthropometric characteristics are important factors that affect swimming performance. The aim of this study is to build a discriminant model using anthropometric factors to identify elite short-to-medium-distance freestyle swimmers through an
Qile Pan +3 more
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The Highly Adaptive Lasso Estimator [PDF]
2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2016 Estimation of a regression functions is a common goal of statistical learning. We propose a novel nonparametric regression estimator that, in contrast to many existing methods, does not rely on local smoothness assumptions nor is it constructed using local smoothing techniques.
David C. Benkeser, Mark J. van der Laan
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Bayesian extensions on Lasso and adaptive Lasso Tobit regressions [PDF]
Periodicals of Engineering and Natural Sciences (PEN), 2020 Since lasso method launched, a lot of applications and extensions were run on it which made it to become deeply widely used in various discipline. In this paper, we proposed the Scale Mixture of Normals mixing with Rayleigh (SMNR) distribution on their variances to represent the double exponential distribution.
Fadel Hamid Hadi Alhusseini +2 more
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AUTALASSO: an automatic adaptive LASSO for genome-wide prediction [PDF]
BMC Bioinformatics, 2019 Background Genome-wide prediction has become the method of choice in animal and plant breeding. Prediction of breeding values and phenotypes are routinely performed using large genomic data sets with number of markers on the order of several thousands to
Patrik Waldmann +5 more
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The prediction of live weight of hair goats through penalized regression methods: LASSO and adaptive LASSO [PDF]
Archives Animal Breeding, 2018 The least absolute selection and shrinkage operator (LASSO) and adaptive LASSO methods have become a popular model in the last decade, especially for data with a multicollinearity problem.
S. Akkol
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Adaptive LASSO in High-dimensions
, 2022 The Least Absolute Shrinkage and Selector operator (LASSO) is a famous method for estimation and predictor selection simultaneously. But in certain situations where the LASSO is not consistent for predictor selection, Zou (2006). Therefore, he suggested a new type of the LASSO, called the adaptive LASSO, where ordinary least squares estimators are used
Abdul Wahid
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Factors Affecting Exclusive Breastfeeding, Using Adaptive LASSO Regression [PDF]
International Journal of Community Based Nursing and Midwifery, 2018 Background: Exclusive breastfeeding (EBF) in the first six months of the life can significantly improve maternal and children health, and it is especially important in low- and middle-income countries.
Najmeh Maharlouei +4 more
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Perturbation bootstrap in adaptive Lasso [PDF]
The Annals of Statistics, 2019 The Adaptive Lasso(Alasso) was proposed by Zou [\textit{J. Amer. Statist. Assoc. \textbf{101} (2006) 1418-1429}] as a modification of the Lasso for the purpose of simultaneous variable selection and estimation of the parameters in a linear regression model.
Das, Debraj +2 more
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Regression shrinkage and selection via least quantile shrinkage and selection operator.
PLoS ONE, 2023 Over recent years, the state-of-the-art lasso and adaptive lasso have aquired remarkable consideration. Unlike the lasso technique, adaptive lasso welcomes the variables' effects in penalty meanwhile specifying adaptive weights to penalize coefficients ...
Alireza Daneshvar, Golalizadeh Mousa
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