| 000 | 03860cam a2200589Ki 4500 | ||
|---|---|---|---|
| 001 | 9781315155289 | ||
| 003 | FlBoTFG | ||
| 005 | 20220509193041.0 | ||
| 006 | m o d | ||
| 007 | cr cnu---unuuu | ||
| 008 | 190308s2019 flu ob 001 0 eng d | ||
| 040 |
_aOCoLC-P _beng _erda _epn _cOCoLC-P |
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| 020 |
_a9781315155289 _q(electronic bk.) |
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| 020 |
_a1315155281 _q(electronic bk.) |
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| 020 |
_a9781351641821 _q(electronic bk. : Mobipocket) |
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| 020 |
_a1351641824 _q(electronic bk. : Mobipocket) |
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| 020 |
_a9781498781626 _q(electronic bk. : PDF) |
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| 020 |
_a1498781624 _q(electronic bk. : PDF) |
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| 020 |
_a9781351651332 _q(electronic bk. : EPUB) |
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| 020 |
_a1351651331 _q(electronic bk. : EPUB) |
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| 020 | _z9781498781619 | ||
| 020 | _z1498781616 | ||
| 035 | _a(OCoLC)1089446088 | ||
| 035 | _a(OCoLC-P)1089446088 | ||
| 050 | 4 |
_aQA360 _b.L37 2019eb |
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| 072 | 7 |
_aMAT _x005000 _2bisacsh |
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| 072 | 7 |
_aMAT _x034000 _2bisacsh |
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_aMAT _x029000 _2bisacsh |
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_aMAT _x036000 _2bisacsh |
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| 072 | 7 |
_aPBT _2bicssc |
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| 082 | 0 | 4 |
_a515/.9 _223 |
| 100 | 1 |
_aLe Roux, Brigitte, _eauthor. |
|
| 245 | 1 | 0 |
_aCombinatorial inference in geometric data analysis / _cBrigitte Le Roux, Solène Bienaise, Jean-Luc Durand. |
| 264 | 1 |
_aBoca Raton, Florida : _bCRC Press, _c[2019] |
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| 300 | _a1 online resource. | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 490 | 0 | _aChapman & Hall/CRC computer science and data analysis series | |
| 520 | _aGeometric Data Analysis designates the approach of Multivariate Statistics that conceptualizes the set of observations as a Euclidean cloud of points. Combinatorial Inference in Geometric Data Analysis gives an overview of multidimensional statistical inference methods applicable to clouds of points that make no assumption on the process of generating data or distributions, and that are not based on random modelling but on permutation procedures recasting in a combinatorial framework. It focuses particularly on the comparison of a group of observations to a reference population (combinatorial test) or to a reference value of a location parameter (geometric test), and on problems of homogeneity, that is the comparison of several groups for two basic designs. These methods involve the use of combinatorial procedures to build a reference set in which we place the data. The chosen test statistics lead to original extensions, such as the geometric interpretation of the observed level, and the construction of a compatibility region. Features: Defines precisely the object under study in the context of multidimensional procedures, that is clouds of points Presents combinatorial tests and related computations with R and Coheris SPAD software Includes four original case studies to illustrate application of the tests Includes necessary mathematical background to ensure it is self-contained This book is suitable for researchers and students of multivariate statistics, as well as applied researchers of various scientific disciplines. It could be used for a specialized course taught at either master or PhD level. | ||
| 588 | _aOCLC-licensed vendor bibliographic record. | ||
| 650 | 0 | _aGeometric analysis. | |
| 650 | 0 | _aCombinatorial analysis. | |
| 650 | 0 | _aStatistics. | |
| 650 | 7 |
_aMATHEMATICS / Calculus _2bisacsh |
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| 650 | 7 |
_aMATHEMATICS / Mathematical Analysis _2bisacsh |
|
| 650 | 7 |
_aMATHEMATICS / Probability & Statistics / General _2bisacsh |
|
| 650 | 7 |
_aMATHEMATICS / Combinatorics _2bisacsh |
|
| 700 | 1 |
_aBienaise, Solène, _d1986- _eauthor. |
|
| 700 | 1 |
_aDurand, Jean-Luc _c(Mathematician), _eauthor. |
|
| 856 | 4 | 0 |
_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9781315155289 |
| 856 | 4 | 2 |
_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf |
| 999 |
_c128882 _d128882 |
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