Results 41 to 50 of about 253,016 (276)

A Pliable Lasso

Journal of Computational and Graphical Statistics, 2019
We propose a generalization of the lasso that allows the model coefficients to vary as a function of a general set of some prespecified modifying variables. These modifiers might be variables such as gender, age, or time. The paradigm is quite general, with each lasso coefficient modified by a sparse linear function of the modifying variables Z.
Tibshirani, Robert, Friedman, Jerome
openaire   +3 more sources

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

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Pick-and-eat space crop production flight testing on the International Space Station

Journal of Plant Interactions
Fresh, nutritious, palatable produce for crew consumption on long-duration spaceflight missions may provide health-promoting, bioavailable nutrients and enhance the dietary experience.
Jess M. Bunchek, Mary E. Hummerick, LaShelle E. Spencer, Matthew W. Romeyn, Millennia Young, Robert C. Morrow, Cary A. Mitchell, Grace L. Douglas, Raymond M. Wheeler, Gioia D. Massa   +9 more
doaj   +1 more source

Predicting the risk of autoimmune thyroid disease in patients with vitiligo: Development and assessment of a new predictive nomogram

Frontiers in Endocrinology, 2023
BackgroundThis study aimed to develop an autoimmune thyroid disease (AITD) risk prediction model for patients with vitiligo based on readily available characteristics.MethodsA retrospective analysis was conducted on the clinical characteristics ...
Ze Ma, Menghan Cai, Kang Yang, Junru Liu, Tao Guo, Xiaojie Liu, Junling Zhang   +6 more
doaj   +1 more source

Identifying gene expression signatures for risk stratification of postoperative adjuvant chemotherapy in colorectal cancer

FEBS Open Bio, EarlyView.
A novel signature integrating genome‐wide analysis with clinical factors predicts recurrence in stage II colorectal cancer and enables a new risk stratification to guide postoperative adjuvant chemotherapy. Clinical risk stratification for postoperative recurrence in patients with pathological stage II (pStage II) colorectal cancer (CRC) is essential ...
Mayuko Otomo, Keisuke Okuno, Shuichi Watanabe, Sakiko Oba, Hiroyasu Kagawa, Masanori Tokunaga, Daisuke Ban, Yusuke Kinugasa   +7 more
wiley   +1 more source

Panorama internacional y regional del lavado de activos y sus impactos sociales, políticos y económicos en Ecuador

Revista de Relaciones Internacionales, Estrategia y Seguridad
La investigación tiene como objetivo analizar el lavado de activos como un fenómeno social contemporáneo en los panoramas internacional y regional, y describir sus efectos sociales, políticos y económicos en Ecuador.
Edison Patricio Cisneros Corrales, Josué Israel Barragán Pacheco   +1 more
doaj   +1 more source

Cross-products LASSO

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
Negative co-occurrence is a common phenomenon in many signal processing applications. In some cases the signals involved are sparse, and this information can be exploited to recover them. In this paper, we present a sparse learning approach that explicitly takes into account negative co-occurrence. This is achieved by adding a novel penalty term to the
Luengo García, David, Vía Rodríguez, Javier, Monzón García, Sandra, Trigano, Tom, Artés Rodríguez, Antonio   +4 more
openaire   +2 more sources

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +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