01712nam0-2200481---450 99000953682040332120211027125412.0978-0-674-99622-9Vol. 1978-0-674-99623-6Vol. 20-674-99623-2Vol. 2000953682FED01000953682(Aleph)000953682FED0100095368220120302g20062007km-y0itay50------bagrcengUSy---a---001gyHesiodedited and translated by Glenn W. MostCambridge, Mass. ; LondonHarvard University Press2006-20072 volumi17 cm<<The >>Loeb classical library57, 503Rilegati con copertina rigida telata1.: LXXXII, 308 p. ; 2.: X, 434 p.1.: Theogony, Works and days, Testimonia. - 2006. - (57)2.: The shield, Catalogue of women, Other fragments. - 2007. - (503)Catalogi, sive Eoeae<in greco e in inglese>54788Opera ed dies<in greco e in inglese>54851Scutum<in greco e in inglese>99385Theogonia<in greco e in inglese>19868881.01Hesiodus<8.-7. sec. a. C.>153091Most,Glenn W.ITUNINAREICATUNIMARCBK990009536820403321P2B-600-LOEB-HES.-200A(1)-2006Bibl.FLFBC10-73371P2B 600 LOEB HES. 200A(2) 200761493FLFBC10-73372FLFBCTheogonia19868Opera ed dies54851Scutum99385Catalogi, sive Eoeae54788UNINA04635nam 22007695 450 991048443700332120250609110705.09789811541032981154103510.1007/978-981-15-4103-2(CKB)4100000011264513(MiAaPQ)EBC6207031(DE-He213)978-981-15-4103-2(MiAaPQ)EBC6420151(Au-PeEL)EBL6420151(OCoLC)1157254545(PPN)248393545(MiAaPQ)EBC6206987(EXLCZ)99410000001126451320200520d2020 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMatrix-Based Introduction to Multivariate Data Analysis /by Kohei Adachi2nd ed. 2020.Singapore :Springer Nature Singapore :Imprint: Springer,2020.1 online resource (457 pages) illustrations9789811541025 9811541027 Includes bibliographical references and index.Elementary matrix operations -- Intravariable statistics -- Inter-variable statistics -- Regression analysis -- Principal component analysis -- Principal component.This 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. In a nutshell, this book allows readers to gain an understanding of the latest developments in multivariate data science.StatisticsStatisticsSocial sciencesStatistical methodsMathematical statisticsData processingComputer scienceMathematicsMathematical statisticsStatistical Theory and MethodsStatistics in Engineering, Physics, Computer Science, Chemistry and Earth SciencesStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public PolicyStatistics and ComputingStatistics in Business, Management, Economics, Finance, InsuranceProbability and Statistics in Computer ScienceStatistics.Statistics.Social sciencesStatistical methods.Mathematical statisticsData processing.Computer scienceMathematics.Mathematical statistics.Statistical Theory and Methods.Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.Statistics and Computing.Statistics in Business, Management, Economics, Finance, Insurance.Probability and Statistics in Computer Science.519.535Adachi Koheiauthttp://id.loc.gov/vocabulary/relators/aut755970MiAaPQMiAaPQMiAaPQBOOK9910484437003321Matrix-based introduction to multivariate data analysis1523448UNINA