The efficiency of modified jackknife and ridge type regression estimators: a comparison [PDF]
Surveys in Mathematics and its Applications, 2008 A common problem in multiple regression models is multicollinearity, which produces undesirable effects on the least squares estimator. To circumvent this problem, two well known estimation procedures are often suggested in the literature.
Sharad Damodar Gore +2 more
doaj
Ridge Estimators for Distributed Lag Models [PDF]
The paper explains how the Almon polynominal lag specification can be made stochastic in two different ways - one suggested by Shiller and another following the lines of Lindley and Smith.
G.S. Maddala
core
POM‐Based Water Splitting Catalyst Under Acid Conditions Driven by Its Assembly on Carbon Nanotubes
Advanced Materials, EarlyView.A newly‐engineered POM‐based electrocatalyst incorporating non‐innocent counter cations exhibits fast kinetics for either the OER or HER under strongly acidic conditions (1 m H2SO4), depending on whether it is assembled on carbon nanotubes (1@CNT) or physically mixed with them (1/CNT). In water‐splitting tests using a two‐electrode setup, these systems
Eugenia P. Quirós‐Díez +8 more
wiley +1 more source
Ridge, a computer program for calculating ridge regression estimates /
, 1977 Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.
Donald E. Hilt, Donald W. Seegrist
openaire +2 more sources
3D‐Printable, Honeycomb‐Inspired Tissue‐Like Bioelectrodes for Patient‐Specific Neural Interface
Advanced Materials, EarlyView.3D printed MRI‐compatible tissue‐like neural electrodes tailored to individual gyral patterns. This honeycomb‐inspired printable gel electrode (HiPGE) employs a bioinspired architecture with soft hydrogels, engineered to match the softness of brain tissue.
Marzia Momin +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.
Esra Akdeniz Duran +2 more
core
Asymmetry of the Ferroelectric Phase Transition in BaTiO3
Advanced Materials, EarlyView.Phase transitions are typically assumed to behave identically in forward and reverse. This work shows that in the ferroelectric material barium titanate this is not true: heating drives an abrupt, first‐order jump, while cooling gives a smooth, continuous change.
Asaf Hershkovitz +14 more
wiley +1 more source
KINERJA JACKKNIFE RIDGE REGRESSION DALAM MENGATASI MULTIKOLINEARITAS
E-Jurnal Matematika, 2014 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
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
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METODE REGRESI RIDGE UNTUK MENGATASI MULTIKOLINIERITAS PADA INDIKATOR KONSTRUKSI DI PROVINSI ACEH [PDF]
, 2017 ABSTRAKPenelitian ini dilakukan untuk mengamati hubungan yang terjadi antara indikator-indikator konstruksi (sebagai variabel bebas), dan nilai konstruksi (sebagai variabel tak bebas).
Siti Zakirah
core