# Orthogonal iteration process of determining K value on estimator of Jackknife ridge regression parameter
> Tinungki G.M.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85074987861
Jurnal / Konferensi: Journal of Physics Conference Series
Tahun terbit: 2019
DOI: https://doi.org/10.1088/1742-6596/1341/9/092001
ISSN: 17426588
Citations: 9

## Authors
- Tinungki G.M.

## Abstract
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 | ( α ˆ ′ GR α ˆ GR ) i − ( α ˆ ′ GR α ˆ GR ) i-1 | ⩽ 0 , 0001 and iteration stops at 5th iteration, so obtain estimator value of generalized ridge coefficient of orthogonal independent variable ( α ˆ _GR ) value of generalized ridge coefficient of orthogonal independent variable ( α ˆ GR ) .

## Keywords
- Algorithm
- Jackknife resampling
- Artificial intelligence
- Computer science
- Mathematics
- Estimator
- Statistics

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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