نمایش نتایج جستجو برای
کلمات کلیدی: Multicollinearity
موارد یافت شده: 21
1 - Enhanced Model Predictions through Principal Components and Average Least Squares-Centered Penalized Regression (چکیده)2 - A new improved Liu estimator for the QSAR model with inverse Gaussian response (چکیده)
3 - Robust biased estimators for Poisson regression model: Simulation and applications (چکیده)
4 - Multicollinearity and Linear Predictor Link Function Problems in Regression Modelling of Longitudinal Data (چکیده)
5 - Liu regression after random forest for prediction and modeling in high dimension (چکیده)
6 - On a generalization of the test of endogeneity in a two stage least squares estimation (چکیده)
7 - Penalized regression via the restricted bridge estimator (چکیده)
8 - SLASSO: a scaled LASSO for multicollinear situations (چکیده)
9 - Feasible Ridge Estimator in Seemingly Unrelated Semiparametric Models (چکیده)
10 - A class of biased estimators based on QR decomposition (چکیده)
11 - Shrinkage ridge regression in partial linear models (چکیده)
12 - New Ridge Regression Estimator in Semiparametric Regression Models (چکیده)
13 - The distribution of the Liu-type estimator of the biasing parameter in elliptically contoured models (چکیده)
14 - Developing a restricted two-parameter Liu-type estimator: A comparison of restricted estimators in the binary logistic regression model (چکیده)
15 - Improved robust ridge M-estimation (چکیده)
16 - Rank-based Liu regression (چکیده)
17 - Some improved estimation strategies in high-dimensional semiparametric regression models with application to riboflavin production data (چکیده)
18 - Preliminary test and Stein-type shrinkage ridge estimators in robust regression (چکیده)
19 - Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High‐Dimension Regime (چکیده)
20 - Generalized Cross-Validation for Simultaneous Optimization of Tuning Parameters in Ridge Regression (چکیده)
21 - The Generalized Maximum Tsallis Entropy Estimators and Applications to the Portland Cement Dataset (چکیده)
