Results 11 to 20 of about 103,730 (259)
The reciprocal Bayesian LASSO [PDF]
Statistics in Medicine, 2021 AbstractA reciprocal LASSO (rLASSO) regularization employs a decreasing penalty function as opposed to conventional penalization approaches that use increasing penalties on the coefficients, leading to stronger parsimony and superior model selection relative to traditional shrinkage methods.
Himel Mallick +3 more
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Hi-LASSO: High-Dimensional LASSO [PDF]
IEEE Access, 2019 High-throughput genomic technologies are leading to a paradigm shift in research of computational biology. Computational analysis with high-dimensional data and its interpretation are essential for the understanding of complex biological systems. Most biological data (e.g., gene expression and DNA sequence data) are high-dimensional, but consist of ...
Youngsoon Kim +4 more
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Cognitive Computation, 2016 Lasso-type variable selection has been demonstrated to be effective in handling high-dimensional data. From the biological perspective, traditional Lasso-type models are capable of learning which stimuli are valuable while ignoring the many that are not, and thus perform feature selection.
Zhihong Zhang 0001 +6 more
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Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China
Remote Sensing, 2021 Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial ...
Simeng Wang, Qihang Liu, Chang Huang
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Canadian Journal of Statistics, 2015 AbstractWe propose a new sparse regression method called thecomponent lasso, based on a simple idea. The method uses the connected‐components structure of the sample covariance matrix to split the problem into smaller ones. It then applies the lasso to each subproblem separately, obtaining a coefficient vector for each one.
Nadine Hussami, Robert Tibshirani
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La Técnica: Revista de las Agrociencias, 2020 Exploitative technological evaluation of the Dongfeng DF 151L motor cultivator in soil preparation for sowing maize Resumen La presente investigación se realizó en la “Finca Juanito”, coordenadas 1o19’46’’ LS y 80o35’3’’ LO, cantón Jipijapa ...
Byron Leonardo Quimís Guerrido +4 more
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Statistics and Computing, 2011 We propose a shrinkage procedure for simultaneous variable selection and estimation in generalized linear models (GLMs) with an explicit predictive motivation. The procedure estimates the coefficients by minimizing the Kullback-Leibler divergence of a set of predictive distributions to the corresponding predictive distributions for the full model ...
Minh-Ngoc Tran +2 more
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Biometrika, 2020 Summary The properties of penalized sample covariance matrices depend on the choice of the penalty function. In this paper, we introduce a class of nonsmooth penalty functions for the sample covariance matrix and demonstrate how their use results in a grouping of the estimated eigenvalues.
Tyler, David E., Yi, Mengxi
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Frontiers in Genetics, 2020 Some candidate genes have been robustly reported to be associated with complex traits, such as the fat mass and obesity-associated (FTO) gene on body mass index (BMI), and the fibroblast growth factor 5 (FGF5) gene on blood pressure levels.
Wan-Yu Lin +10 more
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Algorithms, 2021 Probabilistic solar power forecasting has been critical in Southern Africa because of major shortages of power due to climatic changes and other factors over the past decade. This paper discusses Gaussian process regression (GPR) coupled with core vector
Edina Chandiwana +2 more
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