Applying robust regression techniques to institutional data View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1986-09

AUTHORS

Franz Bingen, Carlos Siau, Peter Rousseeuw

ABSTRACT

Regression techniques are used frequently to analyze the relationships between university activity variables and the needs for different categories of resources. The ordinary least squares method (LS) has the disadvantage of being very sensitive to outliers. As an alternative the least median of squares (LMS) technique is discussed, which can resist a large fraction of contaminated data. To demonstrate the advantages of LMS, the parameters of some regression equations, estimated some years ago by means of ordinary least squares, and describing the needs for nonacademic staff and operating funds in a university, will be reestimated by means of this robust regression technique. More... »

PAGES

277-297

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf00991792

DOI

http://dx.doi.org/10.1007/bf00991792

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028969000


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/2008/0102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Applied Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Vrije Universiteit Brussel", 
          "id": "https://www.grid.ac/institutes/grid.8767.e", 
          "name": [
            "Department of Mathematics, Vrije Universtiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bingen", 
        "givenName": "Franz", 
        "id": "sg:person.015756745456.67", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015756745456.67"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Vrije Universiteit Brussel", 
          "id": "https://www.grid.ac/institutes/grid.8767.e", 
          "name": [
            "Vrije Universtiteit Brussel, Belgium"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Siau", 
        "givenName": "Carlos", 
        "id": "sg:person.011444215656.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011444215656.75"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Delft University of Technology", 
          "id": "https://www.grid.ac/institutes/grid.5292.c", 
          "name": [
            "Delft University of Technology, The Netherlands"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rousseeuw", 
        "givenName": "Peter", 
        "id": "sg:person.0775337371.63", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0775337371.63"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf00976547", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008636143", 
          "https://doi.org/10.1007/bf00976547"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bfb0098492", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034874854", 
          "https://doi.org/10.1007/bfb0098492"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.1982.10477855", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058302678"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.1984.10477105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058302950"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biomet/69.1.242", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059419157"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aoms/1177693054", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064398394"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aos/1176342503", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064406843"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1912810", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069640342"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1986-09", 
    "datePublishedReg": "1986-09-01", 
    "description": "Regression techniques are used frequently to analyze the relationships between university activity variables and the needs for different categories of resources. The ordinary least squares method (LS) has the disadvantage of being very sensitive to outliers. As an alternative the least median of squares (LMS) technique is discussed, which can resist a large fraction of contaminated data. To demonstrate the advantages of LMS, the parameters of some regression equations, estimated some years ago by means of ordinary least squares, and describing the needs for nonacademic staff and operating funds in a university, will be reestimated by means of this robust regression technique.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/bf00991792", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1046373", 
        "issn": [
          "0361-0365", 
          "1573-188X"
        ], 
        "name": "Research in Higher Education", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "25"
      }
    ], 
    "name": "Applying robust regression techniques to institutional data", 
    "pagination": "277-297", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "8a007828a984df46394193609ee5a25f63b78c35982c8a062eb29c3fc61422bc"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf00991792"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1028969000"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf00991792", 
      "https://app.dimensions.ai/details/publication/pub.1028969000"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:35", 
    "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/v90/0000000370_0000000370/records_46775_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007/BF00991792"
  }
]
 

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/bf00991792'

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/bf00991792'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf00991792'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf00991792'


 

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

105 TRIPLES      21 PREDICATES      35 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf00991792 schema:about anzsrc-for:01
2 anzsrc-for:0102
3 schema:author Ncf1c38f764534b4796b05cc6e25aba44
4 schema:citation sg:pub.10.1007/bf00976547
5 sg:pub.10.1007/bfb0098492
6 https://doi.org/10.1080/01621459.1982.10477855
7 https://doi.org/10.1080/01621459.1984.10477105
8 https://doi.org/10.1093/biomet/69.1.242
9 https://doi.org/10.1214/aoms/1177693054
10 https://doi.org/10.1214/aos/1176342503
11 https://doi.org/10.2307/1912810
12 schema:datePublished 1986-09
13 schema:datePublishedReg 1986-09-01
14 schema:description Regression techniques are used frequently to analyze the relationships between university activity variables and the needs for different categories of resources. The ordinary least squares method (LS) has the disadvantage of being very sensitive to outliers. As an alternative the least median of squares (LMS) technique is discussed, which can resist a large fraction of contaminated data. To demonstrate the advantages of LMS, the parameters of some regression equations, estimated some years ago by means of ordinary least squares, and describing the needs for nonacademic staff and operating funds in a university, will be reestimated by means of this robust regression technique.
15 schema:genre research_article
16 schema:inLanguage en
17 schema:isAccessibleForFree false
18 schema:isPartOf N2ad570563c404d558b5697a5c7687257
19 N66fd89618daf4be8b9a014593c5642d6
20 sg:journal.1046373
21 schema:name Applying robust regression techniques to institutional data
22 schema:pagination 277-297
23 schema:productId N297ef898e26d492694c5e03147ad136d
24 N6ebac64af92e4f05be1f55ff4442df4d
25 N887c4584c1024a628e959c20c616890a
26 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028969000
27 https://doi.org/10.1007/bf00991792
28 schema:sdDatePublished 2019-04-11T13:35
29 schema:sdLicense https://scigraph.springernature.com/explorer/license/
30 schema:sdPublisher N78afca9e4f4c4a7aa4f64dc6043b3c39
31 schema:url http://link.springer.com/10.1007/BF00991792
32 sgo:license sg:explorer/license/
33 sgo:sdDataset articles
34 rdf:type schema:ScholarlyArticle
35 N297ef898e26d492694c5e03147ad136d schema:name doi
36 schema:value 10.1007/bf00991792
37 rdf:type schema:PropertyValue
38 N2ad570563c404d558b5697a5c7687257 schema:volumeNumber 25
39 rdf:type schema:PublicationVolume
40 N62596304f6a84a5ba1281b9787f30210 rdf:first sg:person.0775337371.63
41 rdf:rest rdf:nil
42 N66fd89618daf4be8b9a014593c5642d6 schema:issueNumber 3
43 rdf:type schema:PublicationIssue
44 N6ebac64af92e4f05be1f55ff4442df4d schema:name readcube_id
45 schema:value 8a007828a984df46394193609ee5a25f63b78c35982c8a062eb29c3fc61422bc
46 rdf:type schema:PropertyValue
47 N70fa1d9e4ba648559ed3b7be5482ad4e rdf:first sg:person.011444215656.75
48 rdf:rest N62596304f6a84a5ba1281b9787f30210
49 N78afca9e4f4c4a7aa4f64dc6043b3c39 schema:name Springer Nature - SN SciGraph project
50 rdf:type schema:Organization
51 N887c4584c1024a628e959c20c616890a schema:name dimensions_id
52 schema:value pub.1028969000
53 rdf:type schema:PropertyValue
54 Ncf1c38f764534b4796b05cc6e25aba44 rdf:first sg:person.015756745456.67
55 rdf:rest N70fa1d9e4ba648559ed3b7be5482ad4e
56 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
57 schema:name Mathematical Sciences
58 rdf:type schema:DefinedTerm
59 anzsrc-for:0102 schema:inDefinedTermSet anzsrc-for:
60 schema:name Applied Mathematics
61 rdf:type schema:DefinedTerm
62 sg:journal.1046373 schema:issn 0361-0365
63 1573-188X
64 schema:name Research in Higher Education
65 rdf:type schema:Periodical
66 sg:person.011444215656.75 schema:affiliation https://www.grid.ac/institutes/grid.8767.e
67 schema:familyName Siau
68 schema:givenName Carlos
69 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011444215656.75
70 rdf:type schema:Person
71 sg:person.015756745456.67 schema:affiliation https://www.grid.ac/institutes/grid.8767.e
72 schema:familyName Bingen
73 schema:givenName Franz
74 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015756745456.67
75 rdf:type schema:Person
76 sg:person.0775337371.63 schema:affiliation https://www.grid.ac/institutes/grid.5292.c
77 schema:familyName Rousseeuw
78 schema:givenName Peter
79 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0775337371.63
80 rdf:type schema:Person
81 sg:pub.10.1007/bf00976547 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008636143
82 https://doi.org/10.1007/bf00976547
83 rdf:type schema:CreativeWork
84 sg:pub.10.1007/bfb0098492 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034874854
85 https://doi.org/10.1007/bfb0098492
86 rdf:type schema:CreativeWork
87 https://doi.org/10.1080/01621459.1982.10477855 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058302678
88 rdf:type schema:CreativeWork
89 https://doi.org/10.1080/01621459.1984.10477105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058302950
90 rdf:type schema:CreativeWork
91 https://doi.org/10.1093/biomet/69.1.242 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059419157
92 rdf:type schema:CreativeWork
93 https://doi.org/10.1214/aoms/1177693054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064398394
94 rdf:type schema:CreativeWork
95 https://doi.org/10.1214/aos/1176342503 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064406843
96 rdf:type schema:CreativeWork
97 https://doi.org/10.2307/1912810 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069640342
98 rdf:type schema:CreativeWork
99 https://www.grid.ac/institutes/grid.5292.c schema:alternateName Delft University of Technology
100 schema:name Delft University of Technology, The Netherlands
101 rdf:type schema:Organization
102 https://www.grid.ac/institutes/grid.8767.e schema:alternateName Vrije Universiteit Brussel
103 schema:name Department of Mathematics, Vrije Universtiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium
104 Vrije Universtiteit Brussel, Belgium
105 rdf:type schema:Organization
 




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


...