Circular autocorrelation of stationary circular Markov processes View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-10

AUTHORS

Toshihiro Abe, Hiroaki Ogata, Takayuki Shiohama, Hiroyuki Taniai

ABSTRACT

The stationary Markov process is considered and its circular autocorrelation function is investigated. More specifically, the transition density of the stationary Markov circular process is defined by two circular distributions, and we elucidate the structure of the circular autocorrelation when one of these distributions is uniform and the other is arbitrary. The asymptotic properties of the natural estimator of the circular autocorrelation function are derived. Furthermore, we consider the bivariate process of trigonometric functions and provide the explicit form of its spectral density matrix. The validity of the model was assessed by applying it to a series of wind direction data. More... »

PAGES

275-290

References to SciGraph publications

  • 2011-08. Sine-skewed circular distributions in STATISTICAL PAPERS
  • 1991. Time Series: Theory and Methods in NONE
  • 2015-10. On a class of circulas: copulas for circular distributions in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • 1989. The Analysis of Directional Time Series: Applications to Wind Speed and Direction in NONE
  • 2006-09. Hidden Markov models for circular and linear-circular time series in ENVIRONMENTAL AND ECOLOGICAL STATISTICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11203-016-9154-0

    DOI

    http://dx.doi.org/10.1007/s11203-016-9154-0

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1020879028


    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": "Nanzan University", 
              "id": "https://www.grid.ac/institutes/grid.444385.a", 
              "name": [
                "Department of Systems and Mathematical Science, Nanzan University, 18 Yamazato-cho, 446-8673, Showa-ku, Nagoya, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Abe", 
            "givenName": "Toshihiro", 
            "id": "sg:person.012364243415.46", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012364243415.46"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Tokyo Metropolitan University", 
              "id": "https://www.grid.ac/institutes/grid.265074.2", 
              "name": [
                "Department of Business Administration, Tokyo Metropolitan University, 1-1 Minami-Osawa, 192-0397, Hachioji-shi, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ogata", 
            "givenName": "Hiroaki", 
            "id": "sg:person.011725701341.43", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011725701341.43"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Tokyo University of Science", 
              "id": "https://www.grid.ac/institutes/grid.143643.7", 
              "name": [
                "Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, 6-3-1 Niijuku, 125-8585, Katsushika, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Shiohama", 
            "givenName": "Takayuki", 
            "id": "sg:person.016007072006.52", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016007072006.52"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Waseda University", 
              "id": "https://www.grid.ac/institutes/grid.5290.e", 
              "name": [
                "School of International Liberal Studies, Waseda University, 1-6-1 Nishiwaseda, 169-8050, Shinjuku, Tokyo, Japan"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Taniai", 
            "givenName": "Hiroyuki", 
            "id": "sg:person.012037656654.08", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012037656654.08"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1111/j.1467-9892.1994.tb00197.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003445038"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1467-9868.2010.00748.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011309779"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.1467-9868.2010.00748.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011309779"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10651-006-0015-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013359805", 
              "https://doi.org/10.1007/s10651-006-0015-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1034653958", 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4419-0320-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034653958", 
              "https://doi.org/10.1007/978-1-4419-0320-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4419-0320-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034653958", 
              "https://doi.org/10.1007/978-1-4419-0320-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s10463-014-0493-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039040172", 
              "https://doi.org/10.1007/s10463-014-0493-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4612-3688-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044713822", 
              "https://doi.org/10.1007/978-1-4612-3688-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4612-3688-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044713822", 
              "https://doi.org/10.1007/978-1-4612-3688-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rspa.2013.0092", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045739763"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/1467-842x.00131", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050804503"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/1467-842x.00131", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050804503"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00362-009-0277-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052335551", 
              "https://doi.org/10.1007/s00362-009-0277-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/biomet/67.1.255", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059418948"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/biomet/70.2.327", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059419320"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/biomet/asv003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059422201"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1198/016214505000000286", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064198360"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1198/016214505000000286", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064198360"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1198/jasa.2009.tm08313", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064200483"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1214/12-aoas576", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064392914"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3150/11-bej397", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1071056745"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1142/4031", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1098859970"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/9780470316429", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1109489402"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1109489402", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2017-10", 
        "datePublishedReg": "2017-10-01", 
        "description": "The stationary Markov process is considered and its circular autocorrelation function is investigated. More specifically, the transition density of the stationary Markov circular process is defined by two circular distributions, and we elucidate the structure of the circular autocorrelation when one of these distributions is uniform and the other is arbitrary. The asymptotic properties of the natural estimator of the circular autocorrelation function are derived. Furthermore, we consider the bivariate process of trigonometric functions and provide the explicit form of its spectral density matrix. The validity of the model was assessed by applying it to a series of wind direction data.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s11203-016-9154-0", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.5878403", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.6145014", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.6157068", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.5882360", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1136590", 
            "issn": [
              "1387-0874", 
              "1572-9311"
            ], 
            "name": "Statistical Inference for Stochastic Processes", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "20"
          }
        ], 
        "name": "Circular autocorrelation of stationary circular Markov processes", 
        "pagination": "275-290", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "637b03e1c6baf75b36cd256c4feff5fb86a27d15ab1e79703b270fc5114ba2ea"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s11203-016-9154-0"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1020879028"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s11203-016-9154-0", 
          "https://app.dimensions.ai/details/publication/pub.1020879028"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T09:33", 
        "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_99812_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs11203-016-9154-0"
      }
    ]
     

    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/s11203-016-9154-0'

    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/s11203-016-9154-0'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11203-016-9154-0'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11203-016-9154-0'


     

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

    162 TRIPLES      21 PREDICATES      47 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s11203-016-9154-0 schema:about anzsrc-for:01
    2 anzsrc-for:0104
    3 schema:author Nf84ba92e52ea4fdabcc1137a89acfd29
    4 schema:citation sg:pub.10.1007/978-1-4419-0320-4
    5 sg:pub.10.1007/978-1-4612-3688-7
    6 sg:pub.10.1007/s00362-009-0277-x
    7 sg:pub.10.1007/s10463-014-0493-6
    8 sg:pub.10.1007/s10651-006-0015-7
    9 https://app.dimensions.ai/details/publication/pub.1034653958
    10 https://app.dimensions.ai/details/publication/pub.1109489402
    11 https://doi.org/10.1002/9780470316429
    12 https://doi.org/10.1093/biomet/67.1.255
    13 https://doi.org/10.1093/biomet/70.2.327
    14 https://doi.org/10.1093/biomet/asv003
    15 https://doi.org/10.1098/rspa.2013.0092
    16 https://doi.org/10.1111/1467-842x.00131
    17 https://doi.org/10.1111/j.1467-9868.2010.00748.x
    18 https://doi.org/10.1111/j.1467-9892.1994.tb00197.x
    19 https://doi.org/10.1142/4031
    20 https://doi.org/10.1198/016214505000000286
    21 https://doi.org/10.1198/jasa.2009.tm08313
    22 https://doi.org/10.1214/12-aoas576
    23 https://doi.org/10.3150/11-bej397
    24 schema:datePublished 2017-10
    25 schema:datePublishedReg 2017-10-01
    26 schema:description The stationary Markov process is considered and its circular autocorrelation function is investigated. More specifically, the transition density of the stationary Markov circular process is defined by two circular distributions, and we elucidate the structure of the circular autocorrelation when one of these distributions is uniform and the other is arbitrary. The asymptotic properties of the natural estimator of the circular autocorrelation function are derived. Furthermore, we consider the bivariate process of trigonometric functions and provide the explicit form of its spectral density matrix. The validity of the model was assessed by applying it to a series of wind direction data.
    27 schema:genre research_article
    28 schema:inLanguage en
    29 schema:isAccessibleForFree false
    30 schema:isPartOf N474564ed5fef4a6f915e02bd66782695
    31 Nff56512c37c94dceb5ab0243de7c2814
    32 sg:journal.1136590
    33 schema:name Circular autocorrelation of stationary circular Markov processes
    34 schema:pagination 275-290
    35 schema:productId N824e6ac60530442c92710d2f8397a286
    36 N9467f807579a4a57a7e380ecf2a5a65b
    37 Ncc25b58f18c0453ea6f2ea9963601c50
    38 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020879028
    39 https://doi.org/10.1007/s11203-016-9154-0
    40 schema:sdDatePublished 2019-04-11T09:33
    41 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    42 schema:sdPublisher N3651dfc331314fd281322b080e4d6192
    43 schema:url https://link.springer.com/10.1007%2Fs11203-016-9154-0
    44 sgo:license sg:explorer/license/
    45 sgo:sdDataset articles
    46 rdf:type schema:ScholarlyArticle
    47 N2d9c20abeb764232b9c0b6d6655ed472 rdf:first sg:person.011725701341.43
    48 rdf:rest Neff0293c86ba4015a9b0580bfb9efe32
    49 N3651dfc331314fd281322b080e4d6192 schema:name Springer Nature - SN SciGraph project
    50 rdf:type schema:Organization
    51 N37366ebd1e894da3a034ddc535c475e1 rdf:first sg:person.012037656654.08
    52 rdf:rest rdf:nil
    53 N474564ed5fef4a6f915e02bd66782695 schema:issueNumber 3
    54 rdf:type schema:PublicationIssue
    55 N824e6ac60530442c92710d2f8397a286 schema:name doi
    56 schema:value 10.1007/s11203-016-9154-0
    57 rdf:type schema:PropertyValue
    58 N9467f807579a4a57a7e380ecf2a5a65b schema:name dimensions_id
    59 schema:value pub.1020879028
    60 rdf:type schema:PropertyValue
    61 Ncc25b58f18c0453ea6f2ea9963601c50 schema:name readcube_id
    62 schema:value 637b03e1c6baf75b36cd256c4feff5fb86a27d15ab1e79703b270fc5114ba2ea
    63 rdf:type schema:PropertyValue
    64 Neff0293c86ba4015a9b0580bfb9efe32 rdf:first sg:person.016007072006.52
    65 rdf:rest N37366ebd1e894da3a034ddc535c475e1
    66 Nf84ba92e52ea4fdabcc1137a89acfd29 rdf:first sg:person.012364243415.46
    67 rdf:rest N2d9c20abeb764232b9c0b6d6655ed472
    68 Nff56512c37c94dceb5ab0243de7c2814 schema:volumeNumber 20
    69 rdf:type schema:PublicationVolume
    70 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    71 schema:name Mathematical Sciences
    72 rdf:type schema:DefinedTerm
    73 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
    74 schema:name Statistics
    75 rdf:type schema:DefinedTerm
    76 sg:grant.5878403 http://pending.schema.org/fundedItem sg:pub.10.1007/s11203-016-9154-0
    77 rdf:type schema:MonetaryGrant
    78 sg:grant.5882360 http://pending.schema.org/fundedItem sg:pub.10.1007/s11203-016-9154-0
    79 rdf:type schema:MonetaryGrant
    80 sg:grant.6145014 http://pending.schema.org/fundedItem sg:pub.10.1007/s11203-016-9154-0
    81 rdf:type schema:MonetaryGrant
    82 sg:grant.6157068 http://pending.schema.org/fundedItem sg:pub.10.1007/s11203-016-9154-0
    83 rdf:type schema:MonetaryGrant
    84 sg:journal.1136590 schema:issn 1387-0874
    85 1572-9311
    86 schema:name Statistical Inference for Stochastic Processes
    87 rdf:type schema:Periodical
    88 sg:person.011725701341.43 schema:affiliation https://www.grid.ac/institutes/grid.265074.2
    89 schema:familyName Ogata
    90 schema:givenName Hiroaki
    91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011725701341.43
    92 rdf:type schema:Person
    93 sg:person.012037656654.08 schema:affiliation https://www.grid.ac/institutes/grid.5290.e
    94 schema:familyName Taniai
    95 schema:givenName Hiroyuki
    96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012037656654.08
    97 rdf:type schema:Person
    98 sg:person.012364243415.46 schema:affiliation https://www.grid.ac/institutes/grid.444385.a
    99 schema:familyName Abe
    100 schema:givenName Toshihiro
    101 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012364243415.46
    102 rdf:type schema:Person
    103 sg:person.016007072006.52 schema:affiliation https://www.grid.ac/institutes/grid.143643.7
    104 schema:familyName Shiohama
    105 schema:givenName Takayuki
    106 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016007072006.52
    107 rdf:type schema:Person
    108 sg:pub.10.1007/978-1-4419-0320-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034653958
    109 https://doi.org/10.1007/978-1-4419-0320-4
    110 rdf:type schema:CreativeWork
    111 sg:pub.10.1007/978-1-4612-3688-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044713822
    112 https://doi.org/10.1007/978-1-4612-3688-7
    113 rdf:type schema:CreativeWork
    114 sg:pub.10.1007/s00362-009-0277-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1052335551
    115 https://doi.org/10.1007/s00362-009-0277-x
    116 rdf:type schema:CreativeWork
    117 sg:pub.10.1007/s10463-014-0493-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039040172
    118 https://doi.org/10.1007/s10463-014-0493-6
    119 rdf:type schema:CreativeWork
    120 sg:pub.10.1007/s10651-006-0015-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013359805
    121 https://doi.org/10.1007/s10651-006-0015-7
    122 rdf:type schema:CreativeWork
    123 https://app.dimensions.ai/details/publication/pub.1034653958 schema:CreativeWork
    124 https://app.dimensions.ai/details/publication/pub.1109489402 schema:CreativeWork
    125 https://doi.org/10.1002/9780470316429 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109489402
    126 rdf:type schema:CreativeWork
    127 https://doi.org/10.1093/biomet/67.1.255 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059418948
    128 rdf:type schema:CreativeWork
    129 https://doi.org/10.1093/biomet/70.2.327 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059419320
    130 rdf:type schema:CreativeWork
    131 https://doi.org/10.1093/biomet/asv003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059422201
    132 rdf:type schema:CreativeWork
    133 https://doi.org/10.1098/rspa.2013.0092 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045739763
    134 rdf:type schema:CreativeWork
    135 https://doi.org/10.1111/1467-842x.00131 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050804503
    136 rdf:type schema:CreativeWork
    137 https://doi.org/10.1111/j.1467-9868.2010.00748.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011309779
    138 rdf:type schema:CreativeWork
    139 https://doi.org/10.1111/j.1467-9892.1994.tb00197.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1003445038
    140 rdf:type schema:CreativeWork
    141 https://doi.org/10.1142/4031 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098859970
    142 rdf:type schema:CreativeWork
    143 https://doi.org/10.1198/016214505000000286 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064198360
    144 rdf:type schema:CreativeWork
    145 https://doi.org/10.1198/jasa.2009.tm08313 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064200483
    146 rdf:type schema:CreativeWork
    147 https://doi.org/10.1214/12-aoas576 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064392914
    148 rdf:type schema:CreativeWork
    149 https://doi.org/10.3150/11-bej397 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071056745
    150 rdf:type schema:CreativeWork
    151 https://www.grid.ac/institutes/grid.143643.7 schema:alternateName Tokyo University of Science
    152 schema:name Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, 6-3-1 Niijuku, 125-8585, Katsushika, Tokyo, Japan
    153 rdf:type schema:Organization
    154 https://www.grid.ac/institutes/grid.265074.2 schema:alternateName Tokyo Metropolitan University
    155 schema:name Department of Business Administration, Tokyo Metropolitan University, 1-1 Minami-Osawa, 192-0397, Hachioji-shi, Tokyo, Japan
    156 rdf:type schema:Organization
    157 https://www.grid.ac/institutes/grid.444385.a schema:alternateName Nanzan University
    158 schema:name Department of Systems and Mathematical Science, Nanzan University, 18 Yamazato-cho, 446-8673, Showa-ku, Nagoya, Japan
    159 rdf:type schema:Organization
    160 https://www.grid.ac/institutes/grid.5290.e schema:alternateName Waseda University
    161 schema:name School of International Liberal Studies, Waseda University, 1-6-1 Nishiwaseda, 169-8050, Shinjuku, Tokyo, Japan
    162 rdf:type schema:Organization
     




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


    ...