Principal Component Regression Modelling with Variational Bayesian Approach to Overcome Multicollinearity at Various Levels of Missing Data Proportion

Principal Component Regression Modelling with Variational Bayesian Approach to Overcome Multicollinearity at Various Levels of Missing Data Proportion

This study aims to model Principal Component Regression (PCR) using Variational Bayesian Principal Component Analysis (VBPCA) with Ordinary Least Square (OLS) as a method of estimating regression parameters to overcome multicollinearity at various levels of the proportion of missing data. The data u...

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Bibliographic Details
Main Authors: Nabila Azarin Balqis, Suci Astutik, Solimun Solimun
Format: Article
Language:English
Published: Universitas Muhammadiyah Mataram 2022-10-01
Series:JTAM (Jurnal Teori dan Aplikasi Matematika)
Subjects:
missing data
multicollinearity
principal component analysis
principal component regression
variational bayesian pca.
Online Access:http://journal.ummat.ac.id/index.php/jtam/article/view/10223

Internet

http://journal.ummat.ac.id/index.php/jtam/article/view/10223

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