Results 41 to 50 of about 3,727,733 (308)

Efficient Test-based Variable Selection for High-dimensional Linear Models [PDF]

, 2018
Variable selection plays a fundamental role in high-dimensional data analysis. Various methods have been developed for variable selection in recent years.
Gong, Siliang, Liu, Yufeng, Zhang, Kai
core   +3 more sources

Variable Selection by Perfect Sampling

EURASIP Journal on Advances in Signal Processing, 2002
Variable selection is very important in many fields, and for its resolution many procedures have been proposed and investigated. Among them are Bayesian methods that use Markov chain Monte Carlo (MCMC) sampling algorithms.
Huang Yufei, Djurić Petar M
doaj   +1 more source

Variable selection in semiparametric regression modeling

, 2008
In this paper, we are concerned with how to select significant variables in semiparametric modeling. Variable selection for semiparametric regression models consists of two components: model selection for nonparametric components and selection of ...
Li, Runze, Liang, Hua
core   +2 more sources

Gaussian Post-selection for Continuous Variable Quantum Cryptography [PDF]

, 2012
We extend the security proof for continuous variable quantum key distribution protocols using post selection to account for arbitrary eavesdropping attacks by employing the concept of an equivalent protocol where the post-selection is implemented as a ...
F. Grosshans, Nathan Walk, Ping Koy Lam, T. C. Ralph, Thomas Symul, Timothy C. Ralph   +5 more
core   +2 more sources

Gene selection: a Bayesian variable selection approach [PDF]

Bioinformatics, 2003
Abstract Selection of significant genes via expression patterns is an important problem in microarray experiments. Owing to small sample size and the large number of variables (genes), the selection process can be unstable. This paper proposes a hierarchical Bayesian model for gene (variable) selection.
Kyeong Eun, Lee, Naijun, Sha, Edward R, Dougherty, Marina, Vannucci, Bani K, Mallick   +4 more
openaire   +2 more sources

A Quality Improvement Initiative to Standardize Pneumocystis jirovecii Pneumonia Prophylaxis in Pediatric Patients With Solid Tumors

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Pediatric patients with extracranial solid tumors (ST) receiving chemotherapy are at an increased risk for Pneumocystis jirovecii pneumonia (PJP). However, evidence guiding prophylaxis practices in this population is limited. A PJP‐related fatality at our institution highlighted inconsistent prescribing approaches and concerns about
Kriti Kumar, Denise M. Connolly, Ellen Kellington, Elyse Zelunka, Karla Kerrigan, Furqan Shaikh, Paul C. Nathan, Meredith S. Irwin, Sarah Cohen‐Gogo   +8 more
wiley   +1 more source

Sickle Cell Disease Is an Inherent Risk for Asthma in a Sibling Comparison Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction Sickle cell disease (SCD) and asthma share a complex relationship. Although estimates vary, asthma prevalence in children with SCD is believed to be comparable to or higher than the general population. Determining whether SCD confers an increased risk for asthma remains challenging due to overlapping symptoms and the ...
Suhei C. Zuleta De Bernardis, Okeleji Olayinka, Mariam Z. Quraishi, Lakshmi V. Srivaths, Deborah L. Brown, Neethu M. Menon, Ricardo A. Mosquera, Ashwin P. Patel, James M. Stark, Aravind Yadav   +9 more
wiley   +1 more source

Consistency of Bayesian procedures for variable selection

, 2009
It has long been known that for the comparison of pairwise nested models, a decision based on the Bayes factor produces a consistent model selector (in the frequentist sense).
Elías Moreno, F. Javier Girón, George Casella, M. Lina, Martínez   +4 more
core   +2 more sources

Binary and Ordinal Random Effects Models Including Variable Selection [PDF]

, 2010
A likelihood-based boosting approach for fitting binary and ordinal mixed models is presented. In contrast to common procedures it can be used in high-dimensional settings where a large number of potentially influential explanatory variables is available.
Groll, Andreas, Tutz, Gerhard
core   +1 more source

Bayesian One-Sided Variable Selection

Multivariate Behavioral Research, 2020
This paper presents a novel Bayesian variable selection approach that accounts for the sign of the regression coefficients based on multivariate one-sided tests. We propose a truncated g prior to specify a prior distribution of coefficients with anticipated signs in a given model.
Xin Gu, Herbert Hoijtink, Joris Mulder
openaire   +5 more sources