The evaluation of socio-economic development of development agency regions in Turkey using classical and robust principal component analyses

DOI10.1080/02664763.2016.1267115OpenAlexW2563483704MaRDI QIDQ5138758

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Publication date: 4 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2016.1267115

zbMATH Keywords

robust principal component analysisROBPCArobust Mahalanobis distancedevelopment agencysocioeconomic development index

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Modified regression estimators using robust regression methods and covariance matrices in stratified random sampling, A robust EM clustering approach: ROBEM, An improved class of robust ratio estimators by using the minimum covariance determinant estimation, An efficient family of robust-type estimators for the population variance in simple and stratified random sampling

Uses Software

• LIBRA
• ROBPCA
• FSDA

Cites Work

• The DetS and DetMM estimators for multivariate location and scatter
• Identification of Outliers in Multivariate Data
• Principal component analysis based on robust estimators of the covariance or correlation matrix: influence functions and efficiencies
• Unnamed Item