000			01825nam a22002057a 4500
005			20240219190854.0
008			240219b |||||||| |||| 00| 0 eng d
020			_a9780367241032
082			_a519.5354 _bPAG
100			_aPages, Jerome _914449
245			_aMultiple factor analysis by example using R
260			_bCRC Press _aNew York _c2019
300			_axiv, 257 p.
365			_aINR _b2495.00
490			_aChapman & Hall/CRC The R Series
520			_aMultiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR). The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distinction. Focusing on MFA, subsequent chapters examine the key points of MFA in the context of quantitative variables as well as qualitative and mixed data. The author also compares MFA and Procrustes analysis and presents a natural extension of MFA: hierarchical MFA (HMFA). The final chapter explores several elements of matrix calculation and metric spaces used in the book. (https://www.routledge.com/Multiple-Factor-Analysis-by-Example-Using-R/Pags/p/book/9781482205473)
650			_a Factor analysis _916151
650			_aR (Computer program language) _913319
942			_cBK _2ddc
999			_c6199 _d6199