Results 71 to 80 of about 52,512 (299)
A study of local linear ridge regression estimators
, 2011 In the case of the random design nonparametric regression, to correct for the unbounded finite-sample variance of the local linear estimator (LLE), Seifert and Gasser (J. Amer. Statist. Assoc.
鄧文舜; Deng, Wen-shuenn; Chu, C.K.; Cheng, M.Y.
core +1 more source
Advanced Science, EarlyView.This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong +7 more
wiley +1 more source
Semi-Supervised Ridge Regression with Adaptive Graph-Based Label Propagation
Applied Sciences, 2018 In order to overcome the drawbacks of the ridge regression and label propagation algorithms, we propose a new semi-supervised classification method named semi-supervised ridge regression with adaptive graph-based label propagation (SSRR-AGLP).
Yugen Yi +6 more
doaj +1 more source
Corals and Reef‐Dwelling Fish Regulate Carbon Storage and Cycling Processes in Coral Reef Ecosystems
Advanced Science, EarlyView.Coral reefs are biodiversity hotspots, yet their role in carbon storage and cycling remains poorly understood. Using field surveys and modeling in the South China Sea, we reveal the overlooked potential of carbon storage in reef ecosystems and how reef fish, corals, and surface sediment jointly shape reef carbon reservoirs.
Yiting Chen +8 more
wiley +1 more source
Bayesian Analyses of Ridge Regression Prooblems
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2017 A Bayesian formulation of the ridge regression problem is considerd, which derives from a direct specification of prior informations about parameters of general linear regression model when data suffer from a high degree of multicollinearity.A new ...
H. M. Gorgees
doaj
CoRR, 2023 We discuss a boosting approach for the Ridge Regression (RR) method, with applications to the Extreme Learning Machine (ELM), and we show that the proposed method significantly improves the classification performance and robustness of ELMs.
openaire +2 more sources
Advanced Science, EarlyView.Whole‐genome analysis of 1,054 chickens reveals three ancestral sources (NWC, SYA, and SHF) with distinct temporal entry patterns into the Tibetan Plateau. Route‐specific selection scans, calibrated against a demographic null, suggest complementary functional enrichments—vascular homeostasis (NWC), calcium signaling and cardiac adaptation (SYA), and ...
Zongyi Zhao +7 more
wiley +1 more source
Significance testing in ridge regression for genetic data
BMC Bioinformatics, 2011 Background Technological developments have increased the feasibility of large scale genetic association studies. Densely typed genetic markers are obtained using SNP arrays, next-generation sequencing technologies and imputation.
De Iorio Maria, Vineis Paolo, Cule Erika
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Superiority of the MCRR Estimator Over Some Estimators In A Linear Model [PDF]
المجلة العراقية للعلوم الاحصائية, 2011 Modified (r, k) class ridge regression (MCRR) which includes unbiased ridge regression (URR), (r, k) class, principal components regression (PCR) and the ordinary least squares (OLS) estimators is proposed in regression analysis, to overcome the problem ...
Feras Sh. M. Batah
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Biolipid Film‐Fused Electrochemiluminescence for Multipurpose In Situ Bioassays
Advanced Science, EarlyView.An ECL‐emissive, membrane‐interactive scaffold was fabricated, and facilely fused with natural and non‐native phospholipids into multifactorial mimicries of cytomembranes and vesicles for in vitro representative membrane‐process probing. Such a biointerface‐based, state‐sensitive ECL paradigm not only pinpointed proximal phenomena, including channeling
Jialiang Chen +9 more
wiley +1 more source