LEADER 01499nam0-2200469---450 001 990009970420403321 005 20201119132053.0 010 $a978-0-321-41691-9 035 $a000997042 035 $aFED01000997042 035 $a(Aleph)000997042FED01 035 $a000997042 100 $a20150527d2011----km-y0itay50------ba 101 0 $aeng 102 $aGB 105 $aa-------001yy 200 1 $aModern information retrieval$ethe concepts and technology behind search$fRicardo Baeza-Yates, Berthier Ribeiro-Neto 205 $a2nd. ed. 210 $aEngland$cAddison Wesley$dİ2011 215 $axxx, 913 p.$cill.$d24 cm 610 0 $aRecupero delle Informazioni 610 0 $aTecnologie delle Informazioni 676 $a025.04 700 1$aBaeza-Yates,$bRicardo$f<1961- >$027470 701 1$aRibeiro-Neto,$bBerthier$0301937 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990009970420403321 952 $a10 C 583$bBIBLIODIETI 1/2015$fDINEL 952 $a10 C 583A$bBIBLIODIETI64/2016$fDINEL 952 $a10 C 583B$bBIBLIODIETI65/2016$fDINEL 952 $a13 26 22$b3179 / 2020$fFINBC 952 $a13 H 57 12$b3180 / 2020$fFINBC 952 $a13 H 57 13$b3181 / 2020$fFINBC 952 $a23 14 F 15$b3182 / 2020$fFINAG 952 $a23 14 F 16$b3183 / 2020$fFINAG 952 $a23 14 F 17$b3184 / 2020$fFINAG 959 $aDINEL 959 $aFINBC 959 $aFINAG 996 $aModern information retrieval$9733678 997 $aUNINA LEADER 04635nam 22007695 450 001 9910484437003321 005 20250609110705.0 010 $a9789811541032 010 $a9811541035 024 7 $a10.1007/978-981-15-4103-2 035 $a(CKB)4100000011264513 035 $a(MiAaPQ)EBC6207031 035 $a(DE-He213)978-981-15-4103-2 035 $a(MiAaPQ)EBC6420151 035 $a(Au-PeEL)EBL6420151 035 $a(OCoLC)1157254545 035 $a(PPN)248393545 035 $a(MiAaPQ)EBC6206987 035 $a(EXLCZ)994100000011264513 100 $a20200520d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMatrix-Based Introduction to Multivariate Data Analysis /$fby Kohei Adachi 205 $a2nd ed. 2020. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (457 pages) $cillustrations 311 08$a9789811541025 311 08$a9811541027 320 $aIncludes bibliographical references and index. 327 $aElementary matrix operations -- Intravariable statistics -- Inter-variable statistics -- Regression analysis -- Principal component analysis -- Principal component. 330 $aThis is the first textbook that allows readers who may be unfamiliar with matrices to understand a variety of multivariate analysis procedures in matrix forms. By explaining which models underlie particular procedures and what objective function is optimized to fit the model to the data, it enables readers to rapidly comprehend multivariate data analysis. Arranged so that readers can intuitively grasp the purposes for which multivariate analysis procedures are used, the book also offers clear explanations of those purposes, with numerical examples preceding the mathematical descriptions. Supporting the modern matrix formulations by highlighting singular value decomposition among theorems in matrix algebra, this book is useful for undergraduate students who have already learned introductory statistics, as well as for graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis. The book begins byexplaining fundamental matrix operations and the matrix expressions of elementary statistics. Then, it offers an introduction to popular multivariate procedures, with each chapter featuring increasing advanced levels of matrix algebra. Further the book includes in six chapters on advanced procedures, covering advanced matrix operations and recently proposed multivariate procedures, such as sparse estimation, together with a clear explication of the differences between principal components and factor analyses solutions. 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