The paper considers various adhoc assumptions to estimate the ridge parameter k, when the mean squared error (MSE) of ridge estimator is less than the ...
Sep 11, 2008 · The paper considers various adhoc assumptions to estimate the ridge parameter k, when the mean squared error (MSE) of ridge estimator is less ...
Effect of jackknifing on various ridge type estimators | Semantic ...
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The paper considers various adhoc assumptions to estimate the optimal ridge parameter k in the jackknife technique applied in the ridge regression, ...
The paper considers various adhoc assumptions to estimate the ridge parameter k, when the mean squared error (MSE) of ridge estimator is less than the ordinary ...
TL;DR: The paper considers various adhoc assumptions to estimate the optimal ridge parameter k in the jackknife technique applied in the ridge regression, ...
Two stages are involved in the present study. First is a comparison of the two estimators of the jackknifed ridge regression (JRR) and generalized ridge ...
Although jack-knifing reduces bias considerably the jack-knifed ridge estimators have larger variance and may have a larger Mean Square Error than the usual ...
In this paper, a new Jackknifing logistic ridge estimator (NLRE) is proposed and derived. The idea behind the NLRE is to get diagonal matrix with small values ...
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The conditions under which the MJR estimator is better than the other two competing estimators have been investigated. 1 Introduction. One of the major ...
Oct 22, 2024 · The GRR estimation leads to a reduction in the sampling variance, whereas JRR leads to a reduction in the bias. We propose a new estimator, ...