Results 71 to 80 of about 2,638,357 (294)
Recovering Jackknife Ridge Regression Estimates from OLS Results [PDF]
The aim of this paper is addressing or recalculate the estimation methods in multiple linear regression model when there is a problem of Multicollinearity in this model like the ridge regression for Hoerl and Kannard, Baldwin estimator (HKB) and ...
Feras Sh. Mahmood
doaj +1 more source
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka +3 more
wiley +1 more source
KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS
Ordinary least square is a parameter estimations for minimizing residual sum of squares. If the multicollinearity was found in the data, unbias estimator with minimum variance could not be reached.
HANY DEVITA +2 more
doaj +1 more source
Modular, Textile‐Based Soft Robotic Grippers for Agricultural Produce Handling
This article introduces textile‐based pneumatic grippers that transform simple textiles into robust bending actuators. Detailed experiments uncover how cut geometry and fabric selection shape performance. Successful handling of fragile agricultural items showcases the potential of textile robotics for safe, scalable automation in food processing and ...
Zeyu Hou +4 more
wiley +1 more source
ABSTRACT Wetlands constitute Earth's largest natural methane (CH4) source, yet projections of their climate feedback remain uncertain due to poorly constrained temperature sensitivity (Q10‐CH4) of microbial methanogenesis. While water table dynamics have been demonstrated to regulate wetland methanogenesis by altering key soil conditions such as ...
Shuying Qiu +6 more
wiley +1 more source
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
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
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
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.
Wolfgang Karl Härdle +2 more
core
A new Jackknifing ridge estimator for logistic regression model
The ridge regression model has been consistently demonstrated to be an attractive shrinkage method to reduce the effects of multicollinearity. The logistic regression model is a well-known model in application when the response variable is binary data ...
Algamal, Zakariya Y, Hammood, Nawal
core +1 more source

