Results 61 to 70 of about 1,043 (255)
Advanced Science, EarlyView.A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai +3 more
wiley +1 more source
Modified Ridge Regression Estimators
, 2013 Ridge Regression is a variant of ordinary multiple linear regression whose goal is to circumvent the problem of predictors collinearity. It gives-up the Ordinary Least Squares (OLS) estimator as a method for estimating the parameters of the multiple ...
Månsson, Kristofer +2 more
core +1 more source
Regularized Proportional Odds Models [PDF]
, 2011 The proportional odds model is commonly used in regression analysis to predict the outcome for an ordinal response variable. The maximum likelihood approach becomes unstable or even fails in small samples with relatively large number of predictors.
Heumann, Christian +1 more
core +1 more source
Advanced Science, EarlyView.An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen +7 more
wiley +1 more source
, 2008 Multicollinearity, Pitman closeness criterion, r − k class estimator, Ordinary ridge regression estimator, Principal components regression estimator,
Özkale M.R. +5 more
core +1 more source
Advanced Science, EarlyView.This study applied AI to quantify multidimensional body composition from CT images in gastric cancer and healthy controls. Distinct sex‐specific patterns and disease‐related alterations were identified and were associated with survival. Higher muscle and fat measures were linked to improved outcomes.
Tianxiang Li +13 more
wiley +1 more source
Performance of LASSO and Elastic net estimators in Misspecified Linear Regression Model
Ceylon Journal of Science, 2019 Ridge Estimator (RE) has been used as an alternative estimator for Ordinary Least Squared Estimator (OLSE) to handle multicollinearity problem in the linear regression model. However, it introduces heavy bias when the number of predictors is high, and it
M. Kayanan, P. Wijekoon
doaj +1 more source
The Distribution of Stochastic Shrinkage Parameters in Ridge Regression [PDF]
In this article we derive the density and distribution functions of the stochastic shrinkage parameters of three well-known operational Ridge Regression estimators by assuming normality. The stochastic behavior of these parameters is likely to affect the
Luis Firinguetti, Hernán Rubio
core
Quality Thresholds for Angiogenesis Under Acoustic Manipulation in Engineered Vascular Tissues
Advanced Science, EarlyView.Defined biological and physical quality thresholds achieved through acoustic manipulation regulate cellular alignment and spatial organization, promoting self‐assembling vasculature, extracellular matrix deposition, and angiogenic responses, thereby establishing critical acoustic patterning requirements for engineered vascular tissue development in ...
Oscar O'Dwyer Lancaster‐Jones +5 more
wiley +1 more source
, 2016 This paper introduces a new estimator, of ridge parameter k for ridge regression and then evaluated by Monte Carlo simulation. We examine the performance of the proposed estimators compared with other well-known estimators for the model with ...
Dorugade, Ashok Vithoba
core +1 more source