Results 61 to 70 of about 257,684 (210)

Degrees of Freedom for Piecewise Lipschitz Estimators

, 2017
A representation of the degrees of freedom akin to Stein's lemma is given for a class of estimators of a mean value parameter in $\mathbb{R}^n$. Contrary to previous results our representation holds for a range of discontinues estimators.
Hansen, Niels Richard, Mikkelsen, Frederik Riis   +1 more
core   +1 more source

The predictive Lasso

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 ...
Tran, M.-N., Nott, D.J., Leng, C.
openaire   +2 more sources

Transposon sequencing reveals Burkholderia gene fitness in a spaceflight-relevant plant-pathogen interaction

Applied and Environmental Microbiology
The spaceflight environment imparts unique selective pressures on the plants and microbes of plant growth chambers on the International Space Station (ISS), which generally manifests through genetic signatures associated with a heightened response to ...
Anya Volter, Jessica Atkin, Aaron Curry, Anirudha Dixit, Rachel Tucker, Hannah Roberts, Mary Hummerick, Elison B. Blancaflor, Aubrie O'Rourke   +8 more
doaj   +1 more source

Motor imagery classification method based on relative wavelet packet entropy brain network and improved lasso

Frontiers in Neuroscience, 2023
Motor imagery (MI) electroencephalogram (EEG) signals have a low signal-to-noise ratio, which brings challenges in feature extraction and feature selection with high classification accuracy.
Manqing Wang, Manqing Wang, Hui Zhou, Xin Li, Siyu Chen, Dongrui Gao, Dongrui Gao, Yongqing Zhang   +7 more
doaj   +1 more source

Sparse Matrix Inversion with Scaled Lasso [PDF]

, 2013
We propose a new method of learning a sparse nonnegative-definite target matrix. Our primary example of the target matrix is the inverse of a population covariance or correlation matrix.
Sun, Tingni, Zhang, Cun-Hui
core  

A Nonlinear Deep Learning Model for Oxygen Content of Flue Gas

Journal of Harbin University of Science and Technology, 2020
It is a deviation reality that lifespan of some products is described by common distributions. However，the ZZ distribution can better describe the lifespan distribution of this type of product.
TANG Zhenhao, LI Yanyan, CAO Shengxian
doaj   +1 more source

Bayesian Fused Lasso Modeling via Horseshoe Prior [PDF]

, 2022
Yuko Kakikawa, Kaito Shimamura, Shuichi Kawano   +2 more
openalex   +1 more source

A Bootstrap Lasso + Partial Ridge Method to Construct Confidence Intervals for Parameters in High-dimensional Sparse Linear Models

, 2020
Constructing confidence intervals for the coefficients of high-dimensional sparse linear models remains a challenge, mainly because of the complicated limiting distributions of the widely used estimators, such as the lasso.
Li, Jingyi Jessica, Liu, Hanzhong, Xu, Xin   +2 more
core   +1 more source

Don't Fall for Tuning Parameters: Tuning-Free Variable Selection in High Dimensions With the TREX

, 2015
Lasso is a seminal contribution to high-dimensional statistics, but it hinges on a tuning parameter that is difficult to calibrate in practice. A partial remedy for this problem is Square-Root Lasso, because it inherently calibrates to the noise variance.
Lederer, Johannes, Müller, Christian
core   +1 more source

Adding bias to reduce variance in psychological results: A tutorial on penalized regression [PDF]

Tutorials in Quantitative Methods for Psychology, 2017
Regression models are commonly used in psychological research. In most studies, regression coefficients are estimated via maximum likelihood (ML) estimation.
Helwig, Nathaniel E.
doaj   +1 more source