A Fast Algorithm for Robust Principal Components Based on Projection Pursuit View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1996

AUTHORS

C. Croux , A. Ruiz-Gazen

ABSTRACT

One of the aims of a principal component analysis (PCA) is to reduce the dimensionality of a collection of observations. If we plot the first two principal components of the observations, it is often the case that one can already detect the main structure of the data. Another aim is to detect atypical observations in a graphical way, by looking at outlying observations on the principal axes. More... »

PAGES

211-216

References to SciGraph publications

Book

TITLE

COMPSTAT

ISBN

978-3-7908-0953-4
978-3-642-46992-3

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-46992-3_22

DOI

http://dx.doi.org/10.1007/978-3-642-46992-3_22

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1014224380


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0201", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Astronomical and Space Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/02", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Vrije Universiteit Brussel", 
          "id": "https://www.grid.ac/institutes/grid.8767.e", 
          "name": [
            "Faculty of Economics, C.E.M.E., University of Brussels (U.L.B.), C.P.-139, Av. F.D.-Roosevelt 50, B-1050\u00a0Brussels, Belgium"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Croux", 
        "givenName": "C.", 
        "id": "sg:person.015675633543.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015675633543.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Paul Sabatier University", 
          "id": "https://www.grid.ac/institutes/grid.15781.3a", 
          "name": [
            "Laboratoire de Statistique et de Probabilit\u00e9s Route de Narbonne, Universit\u00e9 Paul Sabatier, 31062\u00a0Toulouse Cedex, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ruiz-Gazen", 
        "givenName": "A.", 
        "id": "sg:person.015635363725.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015635363725.42"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1080/10485259508832620", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023856524"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aos/1176349519", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064408863"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-009-5438-0_20", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1089521729", 
          "https://doi.org/10.1007/978-94-009-5438-0_20"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-009-5438-0_20", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1089521729", 
          "https://doi.org/10.1007/978-94-009-5438-0_20"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1996", 
    "datePublishedReg": "1996-01-01", 
    "description": "One of the aims of a principal component analysis (PCA) is to reduce the dimensionality of a collection of observations. If we plot the first two principal components of the observations, it is often the case that one can already detect the main structure of the data. Another aim is to detect atypical observations in a graphical way, by looking at outlying observations on the principal axes.", 
    "editor": [
      {
        "familyName": "Prat", 
        "givenName": "Albert", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-642-46992-3_22", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-7908-0953-4", 
        "978-3-642-46992-3"
      ], 
      "name": "COMPSTAT", 
      "type": "Book"
    }, 
    "name": "A Fast Algorithm for Robust Principal Components Based on Projection Pursuit", 
    "pagination": "211-216", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-642-46992-3_22"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "43c401dc18e3bf4a044e7a874e2f123635a7d90971b51f74f889a4d57c8e7a2c"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1014224380"
        ]
      }
    ], 
    "publisher": {
      "location": "Heidelberg", 
      "name": "Physica-Verlag HD", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-642-46992-3_22", 
      "https://app.dimensions.ai/details/publication/pub.1014224380"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T13:26", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8664_00000251.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-3-642-46992-3_22"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-46992-3_22'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-46992-3_22'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-46992-3_22'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-642-46992-3_22'


 

This table displays all metadata directly associated to this object as RDF triples.

85 TRIPLES      23 PREDICATES      30 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-642-46992-3_22 schema:about anzsrc-for:02
2 anzsrc-for:0201
3 schema:author N9f0cf6036b8141e59a64693559890c8d
4 schema:citation sg:pub.10.1007/978-94-009-5438-0_20
5 https://doi.org/10.1080/10485259508832620
6 https://doi.org/10.1214/aos/1176349519
7 schema:datePublished 1996
8 schema:datePublishedReg 1996-01-01
9 schema:description One of the aims of a principal component analysis (PCA) is to reduce the dimensionality of a collection of observations. If we plot the first two principal components of the observations, it is often the case that one can already detect the main structure of the data. Another aim is to detect atypical observations in a graphical way, by looking at outlying observations on the principal axes.
10 schema:editor Nca8c887bf4554626aa52913c6dda5cce
11 schema:genre chapter
12 schema:inLanguage en
13 schema:isAccessibleForFree false
14 schema:isPartOf N9df1056802ee461289a61ab89d8ba0c0
15 schema:name A Fast Algorithm for Robust Principal Components Based on Projection Pursuit
16 schema:pagination 211-216
17 schema:productId N292cb06839b242c9a86c8fb26b0942be
18 N469a3d26d2594268b94bdcb9e78ba8b6
19 N65fe4afa1ac3431dad5955425f8d49bd
20 schema:publisher N1fe74c750c4248248f7eefde1ea3dba2
21 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014224380
22 https://doi.org/10.1007/978-3-642-46992-3_22
23 schema:sdDatePublished 2019-04-15T13:26
24 schema:sdLicense https://scigraph.springernature.com/explorer/license/
25 schema:sdPublisher Ne77fa087e610498faa04961e6e04b76d
26 schema:url http://link.springer.com/10.1007/978-3-642-46992-3_22
27 sgo:license sg:explorer/license/
28 sgo:sdDataset chapters
29 rdf:type schema:Chapter
30 N098bc20c99984503be2c4eab8ae69638 schema:familyName Prat
31 schema:givenName Albert
32 rdf:type schema:Person
33 N1fe74c750c4248248f7eefde1ea3dba2 schema:location Heidelberg
34 schema:name Physica-Verlag HD
35 rdf:type schema:Organisation
36 N292cb06839b242c9a86c8fb26b0942be schema:name doi
37 schema:value 10.1007/978-3-642-46992-3_22
38 rdf:type schema:PropertyValue
39 N469a3d26d2594268b94bdcb9e78ba8b6 schema:name dimensions_id
40 schema:value pub.1014224380
41 rdf:type schema:PropertyValue
42 N6067900025cc4ef5a89cb46c7f05443c rdf:first sg:person.015635363725.42
43 rdf:rest rdf:nil
44 N65fe4afa1ac3431dad5955425f8d49bd schema:name readcube_id
45 schema:value 43c401dc18e3bf4a044e7a874e2f123635a7d90971b51f74f889a4d57c8e7a2c
46 rdf:type schema:PropertyValue
47 N9df1056802ee461289a61ab89d8ba0c0 schema:isbn 978-3-642-46992-3
48 978-3-7908-0953-4
49 schema:name COMPSTAT
50 rdf:type schema:Book
51 N9f0cf6036b8141e59a64693559890c8d rdf:first sg:person.015675633543.22
52 rdf:rest N6067900025cc4ef5a89cb46c7f05443c
53 Nca8c887bf4554626aa52913c6dda5cce rdf:first N098bc20c99984503be2c4eab8ae69638
54 rdf:rest rdf:nil
55 Ne77fa087e610498faa04961e6e04b76d schema:name Springer Nature - SN SciGraph project
56 rdf:type schema:Organization
57 anzsrc-for:02 schema:inDefinedTermSet anzsrc-for:
58 schema:name Physical Sciences
59 rdf:type schema:DefinedTerm
60 anzsrc-for:0201 schema:inDefinedTermSet anzsrc-for:
61 schema:name Astronomical and Space Sciences
62 rdf:type schema:DefinedTerm
63 sg:person.015635363725.42 schema:affiliation https://www.grid.ac/institutes/grid.15781.3a
64 schema:familyName Ruiz-Gazen
65 schema:givenName A.
66 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015635363725.42
67 rdf:type schema:Person
68 sg:person.015675633543.22 schema:affiliation https://www.grid.ac/institutes/grid.8767.e
69 schema:familyName Croux
70 schema:givenName C.
71 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015675633543.22
72 rdf:type schema:Person
73 sg:pub.10.1007/978-94-009-5438-0_20 schema:sameAs https://app.dimensions.ai/details/publication/pub.1089521729
74 https://doi.org/10.1007/978-94-009-5438-0_20
75 rdf:type schema:CreativeWork
76 https://doi.org/10.1080/10485259508832620 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023856524
77 rdf:type schema:CreativeWork
78 https://doi.org/10.1214/aos/1176349519 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064408863
79 rdf:type schema:CreativeWork
80 https://www.grid.ac/institutes/grid.15781.3a schema:alternateName Paul Sabatier University
81 schema:name Laboratoire de Statistique et de Probabilités Route de Narbonne, Université Paul Sabatier, 31062 Toulouse Cedex, France
82 rdf:type schema:Organization
83 https://www.grid.ac/institutes/grid.8767.e schema:alternateName Vrije Universiteit Brussel
84 schema:name Faculty of Economics, C.E.M.E., University of Brussels (U.L.B.), C.P.-139, Av. F.D.-Roosevelt 50, B-1050 Brussels, Belgium
85 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...