Analysis of multivariate and high-dimensional data:
'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical le...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2014
|
| Schriftenreihe: | Cambridge series on statistical and probabilistic mathematics
32 |
| Links: | https://doi.org/10.1017/CBO9781139025805 |
| Zusammenfassung: | 'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduate students in statistics and researchers in data-rich disciplines. |
| Umfang: | 1 Online-Ressource (xxv, 504 Seiten) |
| ISBN: | 9781139025805 |
Internformat
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| spelling | Koch, Inge 1952- Analysis of multivariate and high-dimensional data Inge Koch, University of Adelaide, Australia Analysis of Multivariate & High-Dimensional Data Cambridge Cambridge University Press 2014 1 Online-Ressource (xxv, 504 Seiten) txt c cr Cambridge series on statistical and probabilistic mathematics 32 'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduate students in statistics and researchers in data-rich disciplines. Erscheint auch als Druck-Ausgabe 9780521887939 |
| spellingShingle | Koch, Inge 1952- Analysis of multivariate and high-dimensional data |
| title | Analysis of multivariate and high-dimensional data |
| title_alt | Analysis of Multivariate & High-Dimensional Data |
| title_auth | Analysis of multivariate and high-dimensional data |
| title_exact_search | Analysis of multivariate and high-dimensional data |
| title_full | Analysis of multivariate and high-dimensional data Inge Koch, University of Adelaide, Australia |
| title_fullStr | Analysis of multivariate and high-dimensional data Inge Koch, University of Adelaide, Australia |
| title_full_unstemmed | Analysis of multivariate and high-dimensional data Inge Koch, University of Adelaide, Australia |
| title_short | Analysis of multivariate and high-dimensional data |
| title_sort | analysis of multivariate and high dimensional data |
| work_keys_str_mv | AT kochinge analysisofmultivariateandhighdimensionaldata AT kochinge analysisofmultivariatehighdimensionaldata |