Orthogonal iteration process of determining K value on estimator of Jackknife ridge regression parameter

Abstract

Jackknife is re-sampling bias estimation method, in predict standard deviations. The principle of the Jackknife method in regression parameters estimation is to eliminate one data and repeat it as much as the number of existing data samples. The step in estimating regression parameter of Jackknife Ridge (JR) was the first to transform data through cantering and scaling process and orthogonalization on independent variables. The second determines initial value k0 and perform the iteration process. The third by transform initial estimator JR and finally by testing the feasibility of the resulting model of Jackknife ridge regression. Results obtained, iteration process is conducted until obtained a value of [equation presented] ≤ 0,0001 and iteration stops at 5th iteration, so obtain estimator value of generalized ridge coefficient of orthogonal independent variable (α-GR) value of generalized ridge coefficient of orthogonal independent variable (αGR).