Results 1 to 10 of about 1,312,626 (282)
Estimation of Error Variance in Regularized Regression Models via Adaptive Lasso
Mathematics, 2022 Estimation of error variance in a regression model is a fundamental problem in statistical modeling and inference. In high-dimensional linear models, variance estimation is a difficult problem, due to the issue of model selection.
Xin Wang, Lingchen Kong, Liqun Wang
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Sparse Damage Detection with Complex Group Lasso and Adaptive Complex Group Lasso
Sensors, 2022 Sparsity-based methods have recently come to the foreground of damage detection applications posing a robust and efficient alternative for traditional approaches.
Vasileios Dimopoulos +2 more
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Annals of the Institute of Statistical Mathematics, 2013 We propose the Bayesian adaptive Lasso (BaLasso) for variable selection and coefficient estimation in linear regression. The BaLasso is adaptive to the signal level by adopting different shrinkage for different coefficients. Furthermore, we provide a model selection machinery for the BaLasso by assessing the posterior conditional mode estimates ...
Leng, C., Tran, M.-N., Nott, D.
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Mapping Haplotype-haplotype Interactions with Adaptive LASSO [PDF]
BMC Genetics, 2010 Background The genetic etiology of complex diseases in human has been commonly viewed as a complex process involving both genetic and environmental factors functioning in a complicated manner.
Li Ming +3 more
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Oracle Efficient Estimation and Forecasting With the Adaptive Lasso and the Adaptive Group Lasso in Vector Autoregressions [PDF]
, 2014 Abstract We show that the adaptive Lasso (aLasso) and the adaptive group Lasso (agLasso) are oracle efficient in stationary vector autoregressions where the number of parameters per equation is smaller than the number of observations. In particular, this means that the parameters are estimated consistently at a √T-rate, that the truly ...
Anders Bredahl Kock
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Electronic Journal of Statistics, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sara van de Geer +2 more
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Journal of Big DataFrom social and economic perspectives, compositional data represent the proportions of various components within a whole, carrying non-negative values and providing only relative information.
Ying Tian +2 more
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Adaptive LASSO-MGARCH for Multivariate Volatility Forecasting
MathematicsThis paper evaluates an Adaptive LASSO-MGARCH model for multivariate volatility forecasting, with applications in green and conventional bonds, equities, energy commodities, and EU carbon allowances.
Yongdeng Xu, Juyi Lyu, Wenna Lu
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Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective
CoRR, 2023 This paper presents a comprehensive exploration of the theoretical properties inherent in the Adaptive Lasso and the Transfer Lasso. The Adaptive Lasso, a well-established method, employs regularization divided by initial estimators and is characterized by asymptotic normality and variable selection consistency.
Masaaki Takada, Hironori Fujisawa
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On the distribution of the adaptive LASSO estimator [PDF]
Journal of Statistical Planning and Inference, 2009 We study the distribution of the adaptive LASSO estimator (Zou (2006)) in finite samples as well as in the large-sample limit. The large-sample distributions are derived both for the case where the adaptive LASSO estimator is tuned to perform conservative model selection as well as for the case where the tuning results in consistent model selection. We
Pötscher, Benedikt M. +1 more
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