Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-21

AUTHORS

Gregor Zens

ABSTRACT

A method for implicit variable selection in mixture-of-experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariates. Robust class membership predictors are identified using a normal gamma prior. The resulting model setup is used in a finite mixture of Bernoulli distributions to find homogenous clusters of women in Mozambique based on their information sources on HIV. Fully Bayesian inference is carried out via the implementation of a Gibbs sampler. More... »

PAGES

1-33

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11634-019-00353-y

DOI

http://dx.doi.org/10.1007/s11634-019-00353-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112283320


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/2008/0104", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Statistics", 
        "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": "Vienna University of Economics and Business", 
          "id": "https://www.grid.ac/institutes/grid.15788.33", 
          "name": [
            "Department of Economics, Vienna University of Economics and Business, Welthandelsplatz 1, 1020, Vienna, Austria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zens", 
        "givenName": "Gregor", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1214/088342305000000016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000022757"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11222-014-9500-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003696325", 
          "https://doi.org/10.1007/s11222-014-9500-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11222-014-9500-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003696325", 
          "https://doi.org/10.1007/s11222-014-9500-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/jae.1249", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004629735"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1368-423x.2004.00125.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005446821"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00357-015-9175-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006994500", 
          "https://doi.org/10.1007/s00357-015-9175-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0893-6080(99)00066-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007538187"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1472-698x-10-15", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012884245", 
          "https://doi.org/10.1186/1472-698x-10-15"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2012.06.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012958862"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2015.12.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015946594"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.csda.2014.10.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016445205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/00949659608811772", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016688162"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.csda.2013.02.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018664622"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02294188", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021242048", 
          "https://doi.org/10.1007/bf02294188"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02294188", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021242048", 
          "https://doi.org/10.1007/bf02294188"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11222-013-9387-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030247991", 
          "https://doi.org/10.1007/s11222-013-9387-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11222-013-9387-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030247991", 
          "https://doi.org/10.1007/s11222-013-9387-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1467-9868.00265", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033505213"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1541-0420.2010.01502.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033583768"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.stamet.2010.01.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042223835"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/08-aoas178", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042255409"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.socscimed.2005.03.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042623126"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.socscimed.2005.03.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042623126"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aos/1016120364", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044899899"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/15-ejs1082", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045720135"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1162/neco.1991.3.1.79", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051027395"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.1972.10482378", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058300978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.1988.10478584", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058303561"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.1993.10476353", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058304437"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2013.829001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058306096"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2014.960967", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058306304"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2014.969425", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058306310"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/07350015.2016.1256217", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058340355"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2015.1092979", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058369010"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biomet/82.4.711", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059420611"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tnnls.2012.2200299", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061718116"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/1026034", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062861996"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/016214501750333063", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064197824"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/016214507000000068", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064198624"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/073500107000000106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064199196"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/1061860031329", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064199358"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/10-ba507", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064391542"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1287/mksc.15.4.321", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064713379"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1913710", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069640912"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/acprof:oso/9780199694587.003.0006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1089177088"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmp.2017.09.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092331376"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.spasta.2018.10.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1107990635"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2018.11.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109810200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2018.11.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109810200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2018.11.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109810200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2018.11.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109812200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2018.11.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109812200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jeconom.2018.11.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109812200"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1994.tb01956.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1994.tb01956.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1995.tb02027.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458925"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1995.tb02027.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458925"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/002224379503200402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110841922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/002224379503200402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110841922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/002224379503200402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110841922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/9780429055911-12", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1112103283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/9780429055911-12", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1112103283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/9780429055911-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1112103296"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/9780429055911-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1112103296"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-02-21", 
    "datePublishedReg": "2019-02-21", 
    "description": "A method for implicit variable selection in mixture-of-experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariates. Robust class membership predictors are identified using a normal gamma prior. The resulting model setup is used in a finite mixture of Bernoulli distributions to find homogenous clusters of women in Mozambique based on their information sources on HIV. Fully Bayesian inference is carried out via the implementation of a Gibbs sampler.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11634-019-00353-y", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1045303", 
        "issn": [
          "1862-5347", 
          "1862-5355"
        ], 
        "name": "Advances in Data Analysis and Classification", 
        "type": "Periodical"
      }
    ], 
    "name": "Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership", 
    "pagination": "1-33", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "60b0cc4a86fc8a66b525a84cdb991905b063a011a343a7bb2edd7be831070634"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11634-019-00353-y"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112283320"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11634-019-00353-y", 
      "https://app.dimensions.ai/details/publication/pub.1112283320"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:31", 
    "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/v90/0000000346_0000000346/records_99803_00000005.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs11634-019-00353-y"
  }
]
 

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/s11634-019-00353-y'

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/s11634-019-00353-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11634-019-00353-y'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11634-019-00353-y'


 

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

209 TRIPLES      21 PREDICATES      74 URIs      16 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11634-019-00353-y schema:about anzsrc-for:01
2 anzsrc-for:0104
3 schema:author N0b2818d150044f1bb018f57e5894ebc9
4 schema:citation sg:pub.10.1007/bf02294188
5 sg:pub.10.1007/s00357-015-9175-1
6 sg:pub.10.1007/s11222-013-9387-3
7 sg:pub.10.1007/s11222-014-9500-2
8 sg:pub.10.1186/1472-698x-10-15
9 https://doi.org/10.1002/jae.1249
10 https://doi.org/10.1016/j.csda.2013.02.012
11 https://doi.org/10.1016/j.csda.2014.10.009
12 https://doi.org/10.1016/j.jeconom.2012.06.012
13 https://doi.org/10.1016/j.jeconom.2015.12.006
14 https://doi.org/10.1016/j.jeconom.2018.11.006
15 https://doi.org/10.1016/j.jeconom.2018.11.007
16 https://doi.org/10.1016/j.jmp.2017.09.005
17 https://doi.org/10.1016/j.socscimed.2005.03.012
18 https://doi.org/10.1016/j.spasta.2018.10.004
19 https://doi.org/10.1016/j.stamet.2010.01.002
20 https://doi.org/10.1016/s0893-6080(99)00066-0
21 https://doi.org/10.1080/00949659608811772
22 https://doi.org/10.1080/01621459.1972.10482378
23 https://doi.org/10.1080/01621459.1988.10478584
24 https://doi.org/10.1080/01621459.1993.10476353
25 https://doi.org/10.1080/01621459.2013.829001
26 https://doi.org/10.1080/01621459.2014.960967
27 https://doi.org/10.1080/01621459.2014.969425
28 https://doi.org/10.1080/07350015.2016.1256217
29 https://doi.org/10.1080/10618600.2015.1092979
30 https://doi.org/10.1093/acprof:oso/9780199694587.003.0006
31 https://doi.org/10.1093/biomet/82.4.711
32 https://doi.org/10.1109/tnnls.2012.2200299
33 https://doi.org/10.1111/1467-9868.00265
34 https://doi.org/10.1111/j.1368-423x.2004.00125.x
35 https://doi.org/10.1111/j.1541-0420.2010.01502.x
36 https://doi.org/10.1111/j.2517-6161.1994.tb01956.x
37 https://doi.org/10.1111/j.2517-6161.1995.tb02027.x
38 https://doi.org/10.1137/1026034
39 https://doi.org/10.1162/neco.1991.3.1.79
40 https://doi.org/10.1177/002224379503200402
41 https://doi.org/10.1198/016214501750333063
42 https://doi.org/10.1198/016214507000000068
43 https://doi.org/10.1198/073500107000000106
44 https://doi.org/10.1198/1061860031329
45 https://doi.org/10.1201/9780429055911-12
46 https://doi.org/10.1201/9780429055911-7
47 https://doi.org/10.1214/08-aoas178
48 https://doi.org/10.1214/088342305000000016
49 https://doi.org/10.1214/10-ba507
50 https://doi.org/10.1214/15-ejs1082
51 https://doi.org/10.1214/aos/1016120364
52 https://doi.org/10.1287/mksc.15.4.321
53 https://doi.org/10.2307/1913710
54 schema:datePublished 2019-02-21
55 schema:datePublishedReg 2019-02-21
56 schema:description A method for implicit variable selection in mixture-of-experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariates. Robust class membership predictors are identified using a normal gamma prior. The resulting model setup is used in a finite mixture of Bernoulli distributions to find homogenous clusters of women in Mozambique based on their information sources on HIV. Fully Bayesian inference is carried out via the implementation of a Gibbs sampler.
57 schema:genre research_article
58 schema:inLanguage en
59 schema:isAccessibleForFree false
60 schema:isPartOf sg:journal.1045303
61 schema:name Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership
62 schema:pagination 1-33
63 schema:productId N3fb69d15c6e14b86bc712facf7452ee4
64 N3fe2e20c8d994c92929506651a26b253
65 Nf050e2a5a0e14170a98dc302b6c98613
66 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112283320
67 https://doi.org/10.1007/s11634-019-00353-y
68 schema:sdDatePublished 2019-04-11T09:31
69 schema:sdLicense https://scigraph.springernature.com/explorer/license/
70 schema:sdPublisher Nf106031715a14bb7bd43d22c6c697741
71 schema:url https://link.springer.com/10.1007%2Fs11634-019-00353-y
72 sgo:license sg:explorer/license/
73 sgo:sdDataset articles
74 rdf:type schema:ScholarlyArticle
75 N0a2e061231ee48c8bf8f46c01ddff98d schema:affiliation https://www.grid.ac/institutes/grid.15788.33
76 schema:familyName Zens
77 schema:givenName Gregor
78 rdf:type schema:Person
79 N0b2818d150044f1bb018f57e5894ebc9 rdf:first N0a2e061231ee48c8bf8f46c01ddff98d
80 rdf:rest rdf:nil
81 N3fb69d15c6e14b86bc712facf7452ee4 schema:name readcube_id
82 schema:value 60b0cc4a86fc8a66b525a84cdb991905b063a011a343a7bb2edd7be831070634
83 rdf:type schema:PropertyValue
84 N3fe2e20c8d994c92929506651a26b253 schema:name dimensions_id
85 schema:value pub.1112283320
86 rdf:type schema:PropertyValue
87 Nf050e2a5a0e14170a98dc302b6c98613 schema:name doi
88 schema:value 10.1007/s11634-019-00353-y
89 rdf:type schema:PropertyValue
90 Nf106031715a14bb7bd43d22c6c697741 schema:name Springer Nature - SN SciGraph project
91 rdf:type schema:Organization
92 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
93 schema:name Mathematical Sciences
94 rdf:type schema:DefinedTerm
95 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
96 schema:name Statistics
97 rdf:type schema:DefinedTerm
98 sg:journal.1045303 schema:issn 1862-5347
99 1862-5355
100 schema:name Advances in Data Analysis and Classification
101 rdf:type schema:Periodical
102 sg:pub.10.1007/bf02294188 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021242048
103 https://doi.org/10.1007/bf02294188
104 rdf:type schema:CreativeWork
105 sg:pub.10.1007/s00357-015-9175-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006994500
106 https://doi.org/10.1007/s00357-015-9175-1
107 rdf:type schema:CreativeWork
108 sg:pub.10.1007/s11222-013-9387-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030247991
109 https://doi.org/10.1007/s11222-013-9387-3
110 rdf:type schema:CreativeWork
111 sg:pub.10.1007/s11222-014-9500-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003696325
112 https://doi.org/10.1007/s11222-014-9500-2
113 rdf:type schema:CreativeWork
114 sg:pub.10.1186/1472-698x-10-15 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012884245
115 https://doi.org/10.1186/1472-698x-10-15
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1002/jae.1249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004629735
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/j.csda.2013.02.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018664622
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/j.csda.2014.10.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016445205
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/j.jeconom.2012.06.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012958862
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.jeconom.2015.12.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015946594
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.jeconom.2018.11.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109812200
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.jeconom.2018.11.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109810200
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.jmp.2017.09.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092331376
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/j.socscimed.2005.03.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042623126
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/j.spasta.2018.10.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107990635
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.stamet.2010.01.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042223835
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/s0893-6080(99)00066-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007538187
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1080/00949659608811772 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016688162
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1080/01621459.1972.10482378 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058300978
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1080/01621459.1988.10478584 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058303561
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1080/01621459.1993.10476353 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058304437
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1080/01621459.2013.829001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058306096
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1080/01621459.2014.960967 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058306304
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1080/01621459.2014.969425 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058306310
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1080/07350015.2016.1256217 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058340355
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1080/10618600.2015.1092979 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058369010
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1093/acprof:oso/9780199694587.003.0006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1089177088
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1093/biomet/82.4.711 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059420611
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1109/tnnls.2012.2200299 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061718116
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1111/1467-9868.00265 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033505213
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1111/j.1368-423x.2004.00125.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1005446821
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1111/j.1541-0420.2010.01502.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1033583768
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1111/j.2517-6161.1994.tb01956.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1110458854
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1111/j.2517-6161.1995.tb02027.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1110458925
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1137/1026034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062861996
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1162/neco.1991.3.1.79 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051027395
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1177/002224379503200402 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110841922
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1198/016214501750333063 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064197824
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1198/016214507000000068 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064198624
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1198/073500107000000106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064199196
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1198/1061860031329 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064199358
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1201/9780429055911-12 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112103283
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1201/9780429055911-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112103296
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1214/08-aoas178 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042255409
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1214/088342305000000016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000022757
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1214/10-ba507 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064391542
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1214/15-ejs1082 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045720135
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1214/aos/1016120364 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044899899
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1287/mksc.15.4.321 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064713379
204 rdf:type schema:CreativeWork
205 https://doi.org/10.2307/1913710 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069640912
206 rdf:type schema:CreativeWork
207 https://www.grid.ac/institutes/grid.15788.33 schema:alternateName Vienna University of Economics and Business
208 schema:name Department of Economics, Vienna University of Economics and Business, Welthandelsplatz 1, 1020, Vienna, Austria
209 rdf:type schema:Organization
 




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


...