A Simulation Study on the Prediction Ability of Biased Regression Methods

• 발행기관: 한국자료분석학회
• 저자명: Jong-Duk Kim
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.4 No.4, 361~371쪽, 전체 11쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2002.12.30

영문 초록

This article examines three biased methods used for predictive modelling: ridge regression, principal component regression and partial least squares regression. A Monte Carlo study is performed to compare the prediction ability of these methods along with ordinary least squares. 48 different situations are considered and the root mean squared error of prediction is computed by using leave-one-out cross-validation for the comparison. Performance of the four methods are compared in detail.

목차

1. Introduction

2. Background

3. Simulation Study

4. Results of the Simulation Study

5. Conclusions

References

키워드

Prediction ability Ridge regression Principal component regression Partial least squares regression