Results 91 to 100 of about 25,104 (288)
An efficient generalized ridge estimator for logistic regression model
In the logistic regression model (LRM), the maximum likelihood estimator (MLE) is commonly employed to estimate unknown model parameters. However, when substantial multicollinearity exists among the explanatory variables, the MLE produces unstable ...
Ахмед Мутлаг Алгбури
doaj +1 more source
A Note on The Moments of Stochastic Shrinkage Parameters in Ridge Regression [PDF]
A common problem in econometric models and multiple regression in general is multicollinearity, which produces undesirable effects on the Least Squares estimators.
Hernán Rubio, Luis Firinguetti
core
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
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
Ridge regression estimators with the problem of multicollinearity
Abstract The study aims to illustrate the negative effect of the Multicollinearity problem upon the specimen, identify the way of Ridge Regression as a way to deal with the Multicollinearity problem, focus on some of the estimators of Ridge regression as (James and Stein, Bhattacharya, Heuristic) and identify which estimator from the previously ...
Maie M. Kamel, Sarah F. Aboud
openaire +1 more source
A CMOS‐compatible ferroelectric transistor harnesses the interplay between stable gate polarization memory and volatile non‐quasi‐static channel charge dynamics to emulate how biological synapses regulate their own plasticity. This brain‐inspired dual‐memory mechanism, realized in a single device, enables a physical reservoir computer that solves ...
Yifan Wang +8 more
wiley +1 more source
Difference based Ridge and Liu type Estimators in Semiparametric Regression Models [PDF]
We consider a difference based ridge regression estimator and a Liu type estimator of the regression parameters in the partial linear semiparametric regression model, y = Xβ + f + ε.
Esra Akdeniz Duran +2 more
core
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
wiley +1 more source
On the Weighted Mixed Almost Unbiased Ridge Estimator in Stochastic Restricted Linear Regression
We introduce the weighted mixed almost unbiased ridge estimator (WMAURE) based on the weighted mixed estimator (WME) (Trenkler and Toutenburg 1990) and the almost unbiased ridge estimator (AURE) (Akdeniz and Erol 2003) in linear regression model.
Chaolin Liu, Hu Yang, Jibo Wu
doaj +1 more source
This work proposes a machine‐vision‐based tool for predicting the thickness of in‐line deposited perovskite films, enabling real‐time decision making to control deposition parameters. The workflow integrates perovskite deposition and annealing with uniformity analysis and minimodule fabrication.
Juan Pablo Velásquez +9 more
wiley +1 more source

