LEADER 02986oam 2200613I 450 001 9910960893303321 005 20240410011813.0 010 $a1-04-021236-0 010 $a0-429-16796-2 024 7 $a10.1201/b18358 035 $a(CKB)2670000000610581 035 $a(EBL)2030642 035 $a(SSID)ssj0001540913 035 $a(PQKBManifestationID)11879561 035 $a(PQKBTitleCode)TC0001540913 035 $a(PQKBWorkID)11533936 035 $a(PQKB)11395080 035 $a(MiAaPQ)EBC2030642 035 $a(OCoLC)907924079 035 $a(EXLCZ)992670000000610581 100 $a20180331h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aRobust methods for data reduction /$fAlessio Farcomeni, Luca Greco 205 $a1st ed. 210 1$aBoca Raton :$cCRC Press,$d[2015] 210 4$dİ2015 215 $a1 online resource (297 p.) 225 0 $aChapman & Hall Book 300 $aDescription based upon print version of record. 311 08$a1-4665-9062-9 311 08$a1-4665-9063-7 320 $aIncludes bibliographical references. 327 $aFront Cover; Dedication; Contents; Preface; Authors; List of Figures; List of Tables; List of Examples and R illustrations; Symbol Description; 1. Introduction and Overview; 2. Multivariate Estimation Methods; Section I: Dimension Reduction; Introduction to Dimension Reduction; 3. Principal Component Analysis; 4. Sparse Robust PCA; 5. Canonical Correlation Analysis; 6. Factor Analysis; Section II: Sample Reduction; Introduction to Sample Reduction; 7. k-means and Model-Based Clustering; 8. Robust Clustering; 9. Robust Model-Based Clustering; 10. Double Clustering; 11. Discriminant Analysis 327 $aA. Use of the Software R for Data ReductionBibliography 330 $aRobust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy 606 $aRobust control 606 $aData reduction$xComputer programs 606 $aDimension reduction (Statistics) 615 0$aRobust control. 615 0$aData reduction$xComputer programs. 615 0$aDimension reduction (Statistics) 676 $a519.5/0285 700 $aFarcomeni$b Alessio$0520688 702 $aGreco$b Luca 801 0$bFlBoTFG 801 1$bFlBoTFG 906 $aBOOK 912 $a9910960893303321 996 $aRobust methods for data reduction$94328032 997 $aUNINA