Results 51 to 60 of about 1,043 (255)

New ridge parameters for ridge regression

open access: yes, 2014
Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinary least squares (OLS) estimator in the presence of multicollinearity. In ridge regression, ridge parameter plays an important role in parameter estimation.
Dorugade, A.V.
core   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

open access: yesAdvanced 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

On the Liu and almost unbiased Liu estimators in the presence of multicollinearity with heteroscedastic or correlated errors [PDF]

open access: yesSurveys in Mathematics and its Applications, 2009
This paper introduces a new biased estimator, namely, almost unbiased Liu estimator (AULE) of β for the multiple linear regression model with heteroscedastics and/or correlated errors and suffers from the problem of multicollinearity.
Mustafa I. Alheety, B. M. Golam Kibria
doaj  

Corals and Reef‐Dwelling Fish Regulate Carbon Storage and Cycling Processes in Coral Reef Ecosystems

open access: yesAdvanced 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

Ridge Regression and Ill-Conditioning

open access: yes, 2014
Hoerl and Kennard (1970) suggested the ridge regression estimator as an alternative to the Ordinary Least Squares (OLS) estimator in the presence of multicollinearity.
Iguernane, Mohamed   +3 more
core   +1 more source

Large‐Scale Genomics Reveals Three‐Source Ancestry and Layered Adaptation to High Altitude in Tibetan Chickens

open access: yesAdvanced 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

a simulation comparison of Ridge regression estimators with Lars

open access: yesپژوهش‌های ریاضی, 2022
Introduction Regression analysis is a common method for modeling relationships between variables. Usually Ordinary Least Squares method is applied to estimate regression model parameters.
Roshanak Alimohammadi, Jaleh Bahari
doaj  

Adjusted ridge estimator and comparison with Kibria’s method in linear regression

open access: yes, 2016
This paper proposes an adjusted ridge regression estimator for β for the linear regression model. The merit of the proposed estimator is that it does not require estimating the ridge parameter k unlike other existing estimators. We compared our estimator
Dorugade, A.V.
core   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

open access: yesAdvanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin   +12 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

open access: yesAdvanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang   +2 more
wiley   +1 more source

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