Results 51 to 60 of about 34,245 (290)

Minimax Multiple Shrinkage Estimation

open access: yesThe Annals of Statistics, 1986
A Stein estimator of the form \[ d_ v(Y)=Y-[(p-2)/\| Y-v\|^ 2](Y-v) \] shrinks Y towards a target \(v\in R^ p\). The paper proposes multiple shrinkage estimators (msest's) for cases where prior information suggests several different choices for the target.
openaire   +3 more sources

Clinical Characteristics and Prognostic Risk Factors for Pediatric B‐Cell Lymphoblastic Lymphoma: A Multicenter Retrospective Cohort Study for China Net Childhood Lymphoma

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background B‐cell lymphoblastic lymphoma (B‐LBL) represents a rare variety of non‐Hodgkin lymphoma, with limited research on its biology, progression, and management. Methods A retrospective analysis was performed on the clinical characteristics of 256 patients aged ≤18 years who received treatment under the China Net Childhood Lymphoma (CNCL)‐
Zhijuan Liu   +20 more
wiley   +1 more source

Interval shrinkage estimation of two-parameter exponential distribution with random censored data [PDF]

open access: yesJournal of Mahani Mathematical Research
The use of the two-parameter exponential distribution model in fitting survival and reliability analysis data in the presence of censored random data has recently attracted the attention of a large number of authors.
Ali Soori   +4 more
doaj   +1 more source

Semi-Parametric Estimation Using Bernstein Polynomial and a Finite Gaussian Mixture Model

open access: yesEntropy, 2022
The central focus of this paper is upon the alleviation of the boundary problem when the probability density function has a bounded support. Mixtures of beta densities have led to different methods of density estimation for data assumed to have compact ...
Salima Helali   +2 more
doaj   +1 more source

Blockwise SURE Shrinkage for Non-Local Means

open access: yes, 2013
In this letter, we investigate the shrinkage problem for the non-local means (NLM) image denoising. In particular, we derive the closed-form of the optimal blockwise shrinkage for NLM that minimizes the Stein's unbiased risk estimator (SURE).
Natarajan, Premkumar   +3 more
core   +1 more source

Glycosylated LGALS3BP is highly secreted by bladder cancer cells and represents a novel urinary disease biomarker

open access: yesMolecular Oncology, EarlyView.
Urinary LGALS3BP is elevated in bladder cancer patients compared to healthy controls as detected by the 1959 antibody–based ELISA. The antibody shows enhanced reactivity to the high‐mannose glycosylated variant secreted by cancer cells treated with kifunensine (KIF).
Asia Pece   +18 more
wiley   +1 more source

Regularized Tyler's Scatter Estimator: Existence, Uniqueness, and Algorithms

open access: yes, 2014
This paper considers the regularized Tyler's scatter estimator for elliptical distributions, which has received considerable attention recently.
Babu, Prabhu   +2 more
core   +1 more source

Carbon portfolio management [PDF]

open access: yes, 2018
The aim of the European Union's Emissions Trading Scheme (EU ETS) is that by 2020, emissions from sectors covered by the EU ETS will be 21% lower than in 2005.
Afonin   +35 more
core   +1 more source

Detection of circulating tumor DNA in colorectal cancer patients using a methylation‐specific droplet digital PCR multiplex

open access: yesMolecular Oncology, EarlyView.
We developed a cost‐effective methylation‐specific droplet digital PCR multiplex assay containing tissue‐conserved and tumor‐specific methylation markers. The assay can detect circulating tumor DNA with high accuracy in patients with localized and metastatic colorectal cancer.
Luisa Matos do Canto   +8 more
wiley   +1 more source

Adaptive Monotone Shrinkage for Regression [PDF]

open access: yes, 2015
We develop an adaptive monotone shrinkage estimator for regression models with the following characteristics: i) dense coefficients with small but important effects; ii) a priori ordering that indicates the probable predictive importance of the features.
Foster, Dean, Ma, Zhuang, Stine, Robert
core  

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