Biased Estimation in Regression: An Evaluation Using Mean Squared Error
From MaRDI portal
Publication:4148689
DOI10.2307/2286229zbMath0369.62070OpenAlexW4245275677MaRDI QIDQ4148689
Publication date: 1977
Full work available at URL: https://doi.org/10.2307/2286229
Related Items (18)
A new algorithm for latent root regression analysis ⋮ Algebraic relationships between classical regression and total least- squares estimation ⋮ Fractional principal components regression: a general approach to biased estimators ⋮ Analysis of the condition number in the raise regression ⋮ A comparison of some new and old robust ridge regression estimators ⋮ Beta ridge regression estimators: simulation and application ⋮ Using ridge regression to estimate factors affecting the number of births. A comparative study ⋮ Group least squares regression for linear models with strongly correlated predictor variables ⋮ Ridge estimation in generalized linear models and proportional hazards regressions ⋮ PMC theorems on PCR-ridge class estimators ⋮ A comparison of biased regression estimators using a pitman nearness criterion ⋮ Transformation of variables and the condition number in ridge estimation ⋮ Using principal components for estimating logistic regression with high-dimensional multicollinear data ⋮ Derived components regression using the BACON algorithm ⋮ Performance of Some New Ridge Regression Estimators ⋮ Combining Unbiased Ridge and Principal Component Regression Estimators ⋮ Common principal components for dependent random vectors ⋮ Minimum mean square error estimation in linear regression
This page was built for publication: Biased Estimation in Regression: An Evaluation Using Mean Squared Error