Results 301 to 310 of about 25,397 (329)
Some of the next articles are maybe not open access.
Combining Unbiased Ridge and Principal Component Regression Estimators
Communications in Statistics - Theory and Methods, 2009In the presence of multicollinearity problem, ordinary least squares (OLS) estimation is inadequate. To circumvent this problem, two well-known estimation procedures often suggested are the unbiased ridge regression (URR) estimator given by Crouse et al. (1995) and the (r, k) class estimator given by Baye and Parker (1984). In this article, we proposed
Batah F.S.M., Özkale M.R., Gore S.D.
openaire +2 more sources
Improved ridge regression estimators for the logistic regression model
Computational Statistics, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Saleh, A. K. Md. E., Kibria, B. M. Golam
openaire +2 more sources
On ecological regression and ridge estimation
Communications in Statistics - Simulation and Computation, 1995This paper focuses on the development of an ecological regression approach for voter transition estimation, avoiding the arbitrary assumptions in Goodman's classical model of ecological regression (Goodman [1959]). In doing this, we further develop previous attempts made at the ridge regression approach, by applying a modified generalized ridge ...
openaire +1 more source
ROBUST RIDGE REGRESSION BASED ON AN M‐ESTIMATOR
Australian Journal of Statistics, 1991SummaryConsider the linear regression model y=β01 +Xβ+ in the usual notation. It is argued that the class of ordinary ridge estimators obtained by shrinking the least squares estimator by the matrix (X1X + kI)‐1X'X is sensitive to outliers in the ^variable.
openaire +1 more source
Ridge regression. discussion and comparison of seven Ridge estimators
2013In the paper, the characteristics of seven different techniques of Ridge Regression are evaluated with respect to the same model. A consumption function with yearly data for Greece is therefore analysed and Monte-Carlo method s employed to check the performance of the estimation methods.
openaire +1 more source
Condition Numbers and Minimax Ridge Regression Estimators
Journal of the American Statistical Association, 1985Abstract Ridge regression was originally formulated with two goals in mind: improvement in mean squared error and numerical stability of the coefficient estimates. Conditions are given under which a minimax ridge regression estimator can also improve numerical stability, a quantity that can be measured with the condition number of the matrix to be ...
openaire +1 more source
A mixed estimator interpretation of ridge regression
Social Science Research, 1982Abstract It is shown that a formal isomorphism between the ridge estimator and the homogeneous case of the Theil-Goldberger mixed estimator leads to a general interpretation of ridge regression as ordinary least squares estimation subject to a prior stochastic constraint that all slope coefficients in the model are zero. Users of ridge regression are
openaire +1 more source
Performance of Some New Ridge Regression Estimators
Communications in Statistics - Simulation and Computation, 2003In the ridge regression analysis, the estimation of ridge parameter k is an important problem. Many methods are available for estimating such a parameter. This article has considered some of these methods and also proposed some new estimators based on generalized ridge regression approach. A simulation study has been made to evaluate the performance of
openaire +1 more source
On the estimation of Bell regression model using ridge estimator
Communications in Statistics Part B: Simulation and Computation, 2023Muhammad Amin +2 more
exaly