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BD-DhAAL |
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20190320112317.0 |
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190320t2019 flua b 001 0 eng |
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|a 2018017447
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|a 9781138316430 (pbk. : alk. paper)
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|a 113831661X (hardback : alk. paper)
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|z 9780429455537 (e-book)
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|z 9780429849015 (ePub ebook)
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| 020 |
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|z 9780429849022 (PDF ebook)
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| 020 |
|
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|z 9780429849008 (Mobipocket ebook)
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| 040 |
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|a DLC
|b eng
|c DLC
|e rda
|d DLC
|d BD-DhAAL
|
| 042 |
|
|
|a pcc
|
| 050 |
0 |
0 |
|a QA76.9.Q36
|b G74 2019
|
| 082 |
0 |
0 |
|a 001.42
|2 23
|
| 100 |
1 |
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|a Greenacre, Michael J.,
|e author.
|9 30226
|
| 245 |
1 |
0 |
|a Compositional data analysis in practice /
|c by Michael Greenacre.
|
| 260 |
|
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|a Boca Raton :
|b CRC Press, Taylor & Francis Group,
|c c2019
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| 300 |
|
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|a xiv, 121 pages :
|b illustrations (some color) ;
|c 24 cm.
|
| 490 |
0 |
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|a Chapman & Hall/CRC interdisciplinary statistics
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| 500 |
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|a "A Chapman & Hall book."
|
| 504 |
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|a Includes bibliographical references and index.
|
| 505 |
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|a What are compositional data, and why are they special? Geometry and visualization of compositional data. Logratio transformations. Properties and distributions of logratios. Regression models involving compositional data. Dimension reduction using logratio analysis. Clustering of compositional data. The problem of zeros, with some solutions. Simplifying the task: variable selection. Case study: Fatty acids of marine amphipods. Appendix A: Theory of compositional data analysis.Appendix B Bibliography of compositional data analysisAppendix C Computation of compositional data analysisAppendix D Glossary of termsAppendix E Epilogue
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| 526 |
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|a ESS
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| 541 |
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|a Parama
|e 34317
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| 650 |
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0 |
|a Quantitative research.
|9 30227
|
| 650 |
|
0 |
|a Principal components analysis.
|9 30228
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| 650 |
|
0 |
|a Electronic data processing.
|9 30229
|
| 852 |
|
|
|a Ayesha Abed Library
|c General Stacks
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| 942 |
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