A Case Study Competition Among Methods for Analyzing Large Spatial Data View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-12-14

AUTHORS

Matthew J. Heaton, Abhirup Datta, Andrew O. Finley, Reinhard Furrer, Joseph Guinness, Rajarshi Guhaniyogi, Florian Gerber, Robert B. Gramacy, Dorit Hammerling, Matthias Katzfuss, Finn Lindgren, Douglas W. Nychka, Furong Sun, Andrew Zammit-Mangion

ABSTRACT

The Gaussian process is an indispensable tool for spatial data analysts. The onset of the “big data” era, however, has lead to the traditional Gaussian process being computationally infeasible for modern spatial data. As such, various alternatives to the full Gaussian process that are more amenable to handling big spatial data have been proposed. These modern methods often exploit low-rank structures and/or multi-core and multi-threaded computing environments to facilitate computation. This study provides, first, an introductory overview of several methods for analyzing large spatial data. Second, this study describes the results of a predictive competition among the described methods as implemented by different groups with strong expertise in the methodology. Specifically, each research group was provided with two training datasets (one simulated and one observed) along with a set of prediction locations. Each group then wrote their own implementation of their method to produce predictions at the given location and each was subsequently run on a common computing environment. The methods were then compared in terms of various predictive diagnostics. Supplementary materials regarding implementation details of the methods and code are available for this article online. More... »

PAGES

1-28

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13253-018-00348-w

DOI

http://dx.doi.org/10.1007/s13253-018-00348-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110639041


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/2008/0806", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information Systems", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Heaton", 
        "givenName": "Matthew J.", 
        "id": "sg:person.0765227716.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0765227716.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Datta", 
        "givenName": "Abhirup", 
        "id": "sg:person.011077706605.65", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011077706605.65"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Finley", 
        "givenName": "Andrew O.", 
        "id": "sg:person.01274230643.41", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01274230643.41"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Furrer", 
        "givenName": "Reinhard", 
        "id": "sg:person.014147376517.67", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014147376517.67"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guinness", 
        "givenName": "Joseph", 
        "id": "sg:person.01177613673.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01177613673.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Guhaniyogi", 
        "givenName": "Rajarshi", 
        "id": "sg:person.012603311037.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012603311037.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gerber", 
        "givenName": "Florian", 
        "id": "sg:person.01337470635.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01337470635.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gramacy", 
        "givenName": "Robert B.", 
        "id": "sg:person.013071211265.65", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013071211265.65"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hammerling", 
        "givenName": "Dorit", 
        "id": "sg:person.013470416543.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013470416543.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Katzfuss", 
        "givenName": "Matthias", 
        "id": "sg:person.0606510673.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0606510673.30"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lindgren", 
        "givenName": "Finn", 
        "id": "sg:person.010744637417.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010744637417.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nychka", 
        "givenName": "Douglas W.", 
        "id": "sg:person.07745505663.08", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07745505663.08"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sun", 
        "givenName": "Furong", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Brigham Young University", 
          "id": "https://www.grid.ac/institutes/grid.253294.b", 
          "name": [
            "Brigham Young University, Provo, UT, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zammit-Mangion", 
        "givenName": "Andrew", 
        "id": "sg:person.01116465771.84", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01116465771.84"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1002/env.1137", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000519092"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9868.2008.00663.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000712505"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/wics.1383", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002026114"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/rssc.12061", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003421697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9868.2011.00777.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005242164"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/11-aoas478", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005983867"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.spasta.2015.01.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006436622"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9868.2008.00700.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007468045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9868.2008.00700.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007468045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9892.2011.00732.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009397452"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1369-7412.2003.05512.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011635382"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.spasta.2015.10.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012075570"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9868.2007.00633.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016913265"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9868.2007.00633.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016913265"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1467-9868.2011.01007.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017386545"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.csda.2008.09.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020640131"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.0006-341x.2000.00013.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021065249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/16-ss115", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022925956"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/00401706.2015.1027067", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024772830"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-2440-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027312764", 
          "https://doi.org/10.1007/978-1-4757-2440-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-2440-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027312764", 
          "https://doi.org/10.1007/978-1-4757-2440-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev-statistics-062713-085831", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028662591"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.isprsjprs.2014.10.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035540446"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4471-0657-9_2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036205425", 
          "https://doi.org/10.1007/978-1-4471-0657-9_2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4471-0657-9_2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036205425", 
          "https://doi.org/10.1007/978-1-4471-0657-9_2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-17086-7_3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036769674", 
          "https://doi.org/10.1007/978-3-642-17086-7_3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11222-016-9627-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041073740", 
          "https://doi.org/10.1007/s11222-016-9627-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biostatistics/kxu005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041325402"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmva.2016.04.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042898432"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmva.2016.04.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042898432"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmva.2016.04.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042898432"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10463-013-0399-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046155708", 
          "https://doi.org/10.1007/s10463-013-0399-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10463-013-0399-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046155708", 
          "https://doi.org/10.1007/s10463-013-0399-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10596-008-9116-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047712685", 
          "https://doi.org/10.1007/s10596-008-9116-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10596-008-9116-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047712685", 
          "https://doi.org/10.1007/s10596-008-9116-8"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.spasta.2013.06.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051167942"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.csda.2008.07.033", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053021857"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/00401706.2015.1102763", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058288264"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2012.746061", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058306004"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2015.1044091", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058306396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2015.1123632", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058306484"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2012.719844", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058368831"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2012.760460", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058368856"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2013.812872", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058368890"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2014.914442", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058368943"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2014.914946", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058368944"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2014.975230", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058368981"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2016.1164534", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058369040"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biomet/69.1.95", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059419177"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biomet/74.4.877", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059419769"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/130941912", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062871419"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/016214504000002014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064198326"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/016214506000000852", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064198554"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/016214506000001437", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064198608"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/016214508000000959", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064198854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/106186006x132178", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064199529"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/jasa.2009.0018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064200350"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/jasa.2011.tm09680", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064200712"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/08-aos676", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064390249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/11-ejs607", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064392555"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/13-aoas627", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064393641"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/16-aoas931", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064395603"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18637/jss.v036.i10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068672553"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18637/jss.v063.i10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068672938"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.18637/jss.v072.i01", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068673095"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3150/14-bej645", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071057046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.spasta.2017.08.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091342451"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/rs10010155", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100584682"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/tgrs.2017.2785240", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100757791"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/00401706.2018.1437474", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100989223"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5705/ss.202018.0005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109872322"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2018.1537924", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110257837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618600.2018.1537924", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110257837"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1988.tb01729.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458574"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.2517-6161.1988.tb01729.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1110458574"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2018-12-14", 
    "datePublishedReg": "2018-12-14", 
    "description": "The Gaussian process is an indispensable tool for spatial data analysts. The onset of the \u201cbig data\u201d era, however, has lead to the traditional Gaussian process being computationally infeasible for modern spatial data. As such, various alternatives to the full Gaussian process that are more amenable to handling big spatial data have been proposed. These modern methods often exploit low-rank structures and/or multi-core and multi-threaded computing environments to facilitate computation. This study provides, first, an introductory overview of several methods for analyzing large spatial data. Second, this study describes the results of a predictive competition among the described methods as implemented by different groups with strong expertise in the methodology. Specifically, each research group was provided with two training datasets (one simulated and one observed) along with a set of prediction locations. Each group then wrote their own implementation of their method to produce predictions at the given location and each was subsequently run on a common computing environment. The methods were then compared in terms of various predictive diagnostics. Supplementary materials regarding implementation details of the methods and code are available for this article online.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s13253-018-00348-w", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7074023", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.3658983", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.5544569", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.4312578", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.4318097", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.7161190", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.6624261", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1134206", 
        "issn": [
          "1085-7117", 
          "1537-2693"
        ], 
        "name": "Journal of Agricultural, Biological and Environmental Statistics", 
        "type": "Periodical"
      }
    ], 
    "name": "A Case Study Competition Among Methods for Analyzing Large Spatial Data", 
    "pagination": "1-28", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "32b6411840c394b2f88c0aa25c9a50bb458af2851c4f8b8473337908e0b72de6"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s13253-018-00348-w"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1110639041"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s13253-018-00348-w", 
      "https://app.dimensions.ai/details/publication/pub.1110639041"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:24", 
    "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/v90/0000000296_0000000296/records_57243_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs13253-018-00348-w"
  }
]
 

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/s13253-018-00348-w'

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/s13253-018-00348-w'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s13253-018-00348-w'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s13253-018-00348-w'


 

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

360 TRIPLES      21 PREDICATES      89 URIs      16 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s13253-018-00348-w schema:about anzsrc-for:08
2 anzsrc-for:0806
3 schema:author Ne6d8ab9c1c7f45488258dce77cbf89f5
4 schema:citation sg:pub.10.1007/978-1-4471-0657-9_2
5 sg:pub.10.1007/978-1-4757-2440-0
6 sg:pub.10.1007/978-3-642-17086-7_3
7 sg:pub.10.1007/s10463-013-0399-8
8 sg:pub.10.1007/s10596-008-9116-8
9 sg:pub.10.1007/s11222-016-9627-4
10 https://doi.org/10.1002/env.1137
11 https://doi.org/10.1002/wics.1383
12 https://doi.org/10.1016/j.csda.2008.07.033
13 https://doi.org/10.1016/j.csda.2008.09.008
14 https://doi.org/10.1016/j.isprsjprs.2014.10.001
15 https://doi.org/10.1016/j.jmva.2016.04.006
16 https://doi.org/10.1016/j.spasta.2013.06.003
17 https://doi.org/10.1016/j.spasta.2015.01.004
18 https://doi.org/10.1016/j.spasta.2015.10.006
19 https://doi.org/10.1016/j.spasta.2017.08.004
20 https://doi.org/10.1046/j.1369-7412.2003.05512.x
21 https://doi.org/10.1080/00401706.2015.1027067
22 https://doi.org/10.1080/00401706.2015.1102763
23 https://doi.org/10.1080/00401706.2018.1437474
24 https://doi.org/10.1080/01621459.2012.746061
25 https://doi.org/10.1080/01621459.2015.1044091
26 https://doi.org/10.1080/01621459.2015.1123632
27 https://doi.org/10.1080/10618600.2012.719844
28 https://doi.org/10.1080/10618600.2012.760460
29 https://doi.org/10.1080/10618600.2013.812872
30 https://doi.org/10.1080/10618600.2014.914442
31 https://doi.org/10.1080/10618600.2014.914946
32 https://doi.org/10.1080/10618600.2014.975230
33 https://doi.org/10.1080/10618600.2016.1164534
34 https://doi.org/10.1080/10618600.2018.1537924
35 https://doi.org/10.1093/biomet/69.1.95
36 https://doi.org/10.1093/biomet/74.4.877
37 https://doi.org/10.1093/biostatistics/kxu005
38 https://doi.org/10.1109/tgrs.2017.2785240
39 https://doi.org/10.1111/j.0006-341x.2000.00013.x
40 https://doi.org/10.1111/j.1467-9868.2007.00633.x
41 https://doi.org/10.1111/j.1467-9868.2008.00663.x
42 https://doi.org/10.1111/j.1467-9868.2008.00700.x
43 https://doi.org/10.1111/j.1467-9868.2011.00777.x
44 https://doi.org/10.1111/j.1467-9868.2011.01007.x
45 https://doi.org/10.1111/j.1467-9892.2011.00732.x
46 https://doi.org/10.1111/j.2517-6161.1988.tb01729.x
47 https://doi.org/10.1111/rssc.12061
48 https://doi.org/10.1137/130941912
49 https://doi.org/10.1146/annurev-statistics-062713-085831
50 https://doi.org/10.1198/016214504000002014
51 https://doi.org/10.1198/016214506000000852
52 https://doi.org/10.1198/016214506000001437
53 https://doi.org/10.1198/016214508000000959
54 https://doi.org/10.1198/106186006x132178
55 https://doi.org/10.1198/jasa.2009.0018
56 https://doi.org/10.1198/jasa.2011.tm09680
57 https://doi.org/10.1214/08-aos676
58 https://doi.org/10.1214/11-aoas478
59 https://doi.org/10.1214/11-ejs607
60 https://doi.org/10.1214/13-aoas627
61 https://doi.org/10.1214/16-aoas931
62 https://doi.org/10.1214/16-ss115
63 https://doi.org/10.18637/jss.v036.i10
64 https://doi.org/10.18637/jss.v063.i10
65 https://doi.org/10.18637/jss.v072.i01
66 https://doi.org/10.3150/14-bej645
67 https://doi.org/10.3390/rs10010155
68 https://doi.org/10.5705/ss.202018.0005
69 schema:datePublished 2018-12-14
70 schema:datePublishedReg 2018-12-14
71 schema:description The Gaussian process is an indispensable tool for spatial data analysts. The onset of the “big data” era, however, has lead to the traditional Gaussian process being computationally infeasible for modern spatial data. As such, various alternatives to the full Gaussian process that are more amenable to handling big spatial data have been proposed. These modern methods often exploit low-rank structures and/or multi-core and multi-threaded computing environments to facilitate computation. This study provides, first, an introductory overview of several methods for analyzing large spatial data. Second, this study describes the results of a predictive competition among the described methods as implemented by different groups with strong expertise in the methodology. Specifically, each research group was provided with two training datasets (one simulated and one observed) along with a set of prediction locations. Each group then wrote their own implementation of their method to produce predictions at the given location and each was subsequently run on a common computing environment. The methods were then compared in terms of various predictive diagnostics. Supplementary materials regarding implementation details of the methods and code are available for this article online.
72 schema:genre research_article
73 schema:inLanguage en
74 schema:isAccessibleForFree true
75 schema:isPartOf sg:journal.1134206
76 schema:name A Case Study Competition Among Methods for Analyzing Large Spatial Data
77 schema:pagination 1-28
78 schema:productId N025ef27d132044eab03352e2447fc2fa
79 N7ac852175115485e8c1bb892a1ef3c75
80 Nbdde1d5c1778443e865437f4e1a2ad98
81 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110639041
82 https://doi.org/10.1007/s13253-018-00348-w
83 schema:sdDatePublished 2019-04-11T08:24
84 schema:sdLicense https://scigraph.springernature.com/explorer/license/
85 schema:sdPublisher N1ea29b6ca762435bbae2e885c2e63b58
86 schema:url https://link.springer.com/10.1007%2Fs13253-018-00348-w
87 sgo:license sg:explorer/license/
88 sgo:sdDataset articles
89 rdf:type schema:ScholarlyArticle
90 N025ef27d132044eab03352e2447fc2fa schema:name dimensions_id
91 schema:value pub.1110639041
92 rdf:type schema:PropertyValue
93 N0d34d666db6d4dd682df5b3d6a27eb22 rdf:first sg:person.013071211265.65
94 rdf:rest N79df9a47ac9541a3962ce0a010317c41
95 N14f09d7144384c37afd01e3676629839 rdf:first sg:person.011077706605.65
96 rdf:rest N66b42621fb534d80b0d1e946d661d2d2
97 N1ea29b6ca762435bbae2e885c2e63b58 schema:name Springer Nature - SN SciGraph project
98 rdf:type schema:Organization
99 N49a9b8e8df554c9c8ed96b2296dc0360 rdf:first sg:person.01337470635.08
100 rdf:rest N0d34d666db6d4dd682df5b3d6a27eb22
101 N58ac4e6ff4be48c5965475745ed5e6c1 rdf:first sg:person.01177613673.46
102 rdf:rest N6ce9f5c9b702438d94ff89788e491616
103 N66b42621fb534d80b0d1e946d661d2d2 rdf:first sg:person.01274230643.41
104 rdf:rest Nb11651a3ce5144909f19900469b62422
105 N6ce9f5c9b702438d94ff89788e491616 rdf:first sg:person.012603311037.27
106 rdf:rest N49a9b8e8df554c9c8ed96b2296dc0360
107 N79df9a47ac9541a3962ce0a010317c41 rdf:first sg:person.013470416543.50
108 rdf:rest Nf092ea7a47c242de9191ac636aae6106
109 N7ac852175115485e8c1bb892a1ef3c75 schema:name doi
110 schema:value 10.1007/s13253-018-00348-w
111 rdf:type schema:PropertyValue
112 N7cd5d9239c8e4a748cbc2ea51222fc40 rdf:first sg:person.07745505663.08
113 rdf:rest Nf005d91750104a5882d7c31915717102
114 N7f56368e8d5c4983b0cc84ca044b7a0b rdf:first sg:person.010744637417.62
115 rdf:rest N7cd5d9239c8e4a748cbc2ea51222fc40
116 Na16d5d39d77f445d92fd4839c78f6c85 rdf:first sg:person.01116465771.84
117 rdf:rest rdf:nil
118 Na5f1018a86984362bcc1cecfa54e6208 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
119 schema:familyName Sun
120 schema:givenName Furong
121 rdf:type schema:Person
122 Nb11651a3ce5144909f19900469b62422 rdf:first sg:person.014147376517.67
123 rdf:rest N58ac4e6ff4be48c5965475745ed5e6c1
124 Nbdde1d5c1778443e865437f4e1a2ad98 schema:name readcube_id
125 schema:value 32b6411840c394b2f88c0aa25c9a50bb458af2851c4f8b8473337908e0b72de6
126 rdf:type schema:PropertyValue
127 Ne6d8ab9c1c7f45488258dce77cbf89f5 rdf:first sg:person.0765227716.52
128 rdf:rest N14f09d7144384c37afd01e3676629839
129 Nf005d91750104a5882d7c31915717102 rdf:first Na5f1018a86984362bcc1cecfa54e6208
130 rdf:rest Na16d5d39d77f445d92fd4839c78f6c85
131 Nf092ea7a47c242de9191ac636aae6106 rdf:first sg:person.0606510673.30
132 rdf:rest N7f56368e8d5c4983b0cc84ca044b7a0b
133 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
134 schema:name Information and Computing Sciences
135 rdf:type schema:DefinedTerm
136 anzsrc-for:0806 schema:inDefinedTermSet anzsrc-for:
137 schema:name Information Systems
138 rdf:type schema:DefinedTerm
139 sg:grant.3658983 http://pending.schema.org/fundedItem sg:pub.10.1007/s13253-018-00348-w
140 rdf:type schema:MonetaryGrant
141 sg:grant.4312578 http://pending.schema.org/fundedItem sg:pub.10.1007/s13253-018-00348-w
142 rdf:type schema:MonetaryGrant
143 sg:grant.4318097 http://pending.schema.org/fundedItem sg:pub.10.1007/s13253-018-00348-w
144 rdf:type schema:MonetaryGrant
145 sg:grant.5544569 http://pending.schema.org/fundedItem sg:pub.10.1007/s13253-018-00348-w
146 rdf:type schema:MonetaryGrant
147 sg:grant.6624261 http://pending.schema.org/fundedItem sg:pub.10.1007/s13253-018-00348-w
148 rdf:type schema:MonetaryGrant
149 sg:grant.7074023 http://pending.schema.org/fundedItem sg:pub.10.1007/s13253-018-00348-w
150 rdf:type schema:MonetaryGrant
151 sg:grant.7161190 http://pending.schema.org/fundedItem sg:pub.10.1007/s13253-018-00348-w
152 rdf:type schema:MonetaryGrant
153 sg:journal.1134206 schema:issn 1085-7117
154 1537-2693
155 schema:name Journal of Agricultural, Biological and Environmental Statistics
156 rdf:type schema:Periodical
157 sg:person.010744637417.62 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
158 schema:familyName Lindgren
159 schema:givenName Finn
160 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010744637417.62
161 rdf:type schema:Person
162 sg:person.011077706605.65 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
163 schema:familyName Datta
164 schema:givenName Abhirup
165 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011077706605.65
166 rdf:type schema:Person
167 sg:person.01116465771.84 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
168 schema:familyName Zammit-Mangion
169 schema:givenName Andrew
170 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01116465771.84
171 rdf:type schema:Person
172 sg:person.01177613673.46 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
173 schema:familyName Guinness
174 schema:givenName Joseph
175 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01177613673.46
176 rdf:type schema:Person
177 sg:person.012603311037.27 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
178 schema:familyName Guhaniyogi
179 schema:givenName Rajarshi
180 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012603311037.27
181 rdf:type schema:Person
182 sg:person.01274230643.41 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
183 schema:familyName Finley
184 schema:givenName Andrew O.
185 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01274230643.41
186 rdf:type schema:Person
187 sg:person.013071211265.65 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
188 schema:familyName Gramacy
189 schema:givenName Robert B.
190 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013071211265.65
191 rdf:type schema:Person
192 sg:person.01337470635.08 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
193 schema:familyName Gerber
194 schema:givenName Florian
195 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01337470635.08
196 rdf:type schema:Person
197 sg:person.013470416543.50 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
198 schema:familyName Hammerling
199 schema:givenName Dorit
200 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013470416543.50
201 rdf:type schema:Person
202 sg:person.014147376517.67 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
203 schema:familyName Furrer
204 schema:givenName Reinhard
205 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014147376517.67
206 rdf:type schema:Person
207 sg:person.0606510673.30 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
208 schema:familyName Katzfuss
209 schema:givenName Matthias
210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0606510673.30
211 rdf:type schema:Person
212 sg:person.0765227716.52 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
213 schema:familyName Heaton
214 schema:givenName Matthew J.
215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0765227716.52
216 rdf:type schema:Person
217 sg:person.07745505663.08 schema:affiliation https://www.grid.ac/institutes/grid.253294.b
218 schema:familyName Nychka
219 schema:givenName Douglas W.
220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07745505663.08
221 rdf:type schema:Person
222 sg:pub.10.1007/978-1-4471-0657-9_2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036205425
223 https://doi.org/10.1007/978-1-4471-0657-9_2
224 rdf:type schema:CreativeWork
225 sg:pub.10.1007/978-1-4757-2440-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027312764
226 https://doi.org/10.1007/978-1-4757-2440-0
227 rdf:type schema:CreativeWork
228 sg:pub.10.1007/978-3-642-17086-7_3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036769674
229 https://doi.org/10.1007/978-3-642-17086-7_3
230 rdf:type schema:CreativeWork
231 sg:pub.10.1007/s10463-013-0399-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046155708
232 https://doi.org/10.1007/s10463-013-0399-8
233 rdf:type schema:CreativeWork
234 sg:pub.10.1007/s10596-008-9116-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047712685
235 https://doi.org/10.1007/s10596-008-9116-8
236 rdf:type schema:CreativeWork
237 sg:pub.10.1007/s11222-016-9627-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041073740
238 https://doi.org/10.1007/s11222-016-9627-4
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1002/env.1137 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000519092
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1002/wics.1383 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002026114
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1016/j.csda.2008.07.033 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053021857
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1016/j.csda.2008.09.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020640131
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1016/j.isprsjprs.2014.10.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035540446
249 rdf:type schema:CreativeWork
250 https://doi.org/10.1016/j.jmva.2016.04.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042898432
251 rdf:type schema:CreativeWork
252 https://doi.org/10.1016/j.spasta.2013.06.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051167942
253 rdf:type schema:CreativeWork
254 https://doi.org/10.1016/j.spasta.2015.01.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006436622
255 rdf:type schema:CreativeWork
256 https://doi.org/10.1016/j.spasta.2015.10.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012075570
257 rdf:type schema:CreativeWork
258 https://doi.org/10.1016/j.spasta.2017.08.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091342451
259 rdf:type schema:CreativeWork
260 https://doi.org/10.1046/j.1369-7412.2003.05512.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011635382
261 rdf:type schema:CreativeWork
262 https://doi.org/10.1080/00401706.2015.1027067 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024772830
263 rdf:type schema:CreativeWork
264 https://doi.org/10.1080/00401706.2015.1102763 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058288264
265 rdf:type schema:CreativeWork
266 https://doi.org/10.1080/00401706.2018.1437474 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100989223
267 rdf:type schema:CreativeWork
268 https://doi.org/10.1080/01621459.2012.746061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058306004
269 rdf:type schema:CreativeWork
270 https://doi.org/10.1080/01621459.2015.1044091 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058306396
271 rdf:type schema:CreativeWork
272 https://doi.org/10.1080/01621459.2015.1123632 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058306484
273 rdf:type schema:CreativeWork
274 https://doi.org/10.1080/10618600.2012.719844 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058368831
275 rdf:type schema:CreativeWork
276 https://doi.org/10.1080/10618600.2012.760460 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058368856
277 rdf:type schema:CreativeWork
278 https://doi.org/10.1080/10618600.2013.812872 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058368890
279 rdf:type schema:CreativeWork
280 https://doi.org/10.1080/10618600.2014.914442 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058368943
281 rdf:type schema:CreativeWork
282 https://doi.org/10.1080/10618600.2014.914946 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058368944
283 rdf:type schema:CreativeWork
284 https://doi.org/10.1080/10618600.2014.975230 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058368981
285 rdf:type schema:CreativeWork
286 https://doi.org/10.1080/10618600.2016.1164534 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058369040
287 rdf:type schema:CreativeWork
288 https://doi.org/10.1080/10618600.2018.1537924 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110257837
289 rdf:type schema:CreativeWork
290 https://doi.org/10.1093/biomet/69.1.95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059419177
291 rdf:type schema:CreativeWork
292 https://doi.org/10.1093/biomet/74.4.877 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059419769
293 rdf:type schema:CreativeWork
294 https://doi.org/10.1093/biostatistics/kxu005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041325402
295 rdf:type schema:CreativeWork
296 https://doi.org/10.1109/tgrs.2017.2785240 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100757791
297 rdf:type schema:CreativeWork
298 https://doi.org/10.1111/j.0006-341x.2000.00013.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021065249
299 rdf:type schema:CreativeWork
300 https://doi.org/10.1111/j.1467-9868.2007.00633.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1016913265
301 rdf:type schema:CreativeWork
302 https://doi.org/10.1111/j.1467-9868.2008.00663.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1000712505
303 rdf:type schema:CreativeWork
304 https://doi.org/10.1111/j.1467-9868.2008.00700.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1007468045
305 rdf:type schema:CreativeWork
306 https://doi.org/10.1111/j.1467-9868.2011.00777.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1005242164
307 rdf:type schema:CreativeWork
308 https://doi.org/10.1111/j.1467-9868.2011.01007.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1017386545
309 rdf:type schema:CreativeWork
310 https://doi.org/10.1111/j.1467-9892.2011.00732.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1009397452
311 rdf:type schema:CreativeWork
312 https://doi.org/10.1111/j.2517-6161.1988.tb01729.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1110458574
313 rdf:type schema:CreativeWork
314 https://doi.org/10.1111/rssc.12061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003421697
315 rdf:type schema:CreativeWork
316 https://doi.org/10.1137/130941912 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062871419
317 rdf:type schema:CreativeWork
318 https://doi.org/10.1146/annurev-statistics-062713-085831 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028662591
319 rdf:type schema:CreativeWork
320 https://doi.org/10.1198/016214504000002014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064198326
321 rdf:type schema:CreativeWork
322 https://doi.org/10.1198/016214506000000852 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064198554
323 rdf:type schema:CreativeWork
324 https://doi.org/10.1198/016214506000001437 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064198608
325 rdf:type schema:CreativeWork
326 https://doi.org/10.1198/016214508000000959 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064198854
327 rdf:type schema:CreativeWork
328 https://doi.org/10.1198/106186006x132178 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064199529
329 rdf:type schema:CreativeWork
330 https://doi.org/10.1198/jasa.2009.0018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064200350
331 rdf:type schema:CreativeWork
332 https://doi.org/10.1198/jasa.2011.tm09680 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064200712
333 rdf:type schema:CreativeWork
334 https://doi.org/10.1214/08-aos676 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064390249
335 rdf:type schema:CreativeWork
336 https://doi.org/10.1214/11-aoas478 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005983867
337 rdf:type schema:CreativeWork
338 https://doi.org/10.1214/11-ejs607 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064392555
339 rdf:type schema:CreativeWork
340 https://doi.org/10.1214/13-aoas627 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064393641
341 rdf:type schema:CreativeWork
342 https://doi.org/10.1214/16-aoas931 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064395603
343 rdf:type schema:CreativeWork
344 https://doi.org/10.1214/16-ss115 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022925956
345 rdf:type schema:CreativeWork
346 https://doi.org/10.18637/jss.v036.i10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068672553
347 rdf:type schema:CreativeWork
348 https://doi.org/10.18637/jss.v063.i10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068672938
349 rdf:type schema:CreativeWork
350 https://doi.org/10.18637/jss.v072.i01 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068673095
351 rdf:type schema:CreativeWork
352 https://doi.org/10.3150/14-bej645 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071057046
353 rdf:type schema:CreativeWork
354 https://doi.org/10.3390/rs10010155 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100584682
355 rdf:type schema:CreativeWork
356 https://doi.org/10.5705/ss.202018.0005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109872322
357 rdf:type schema:CreativeWork
358 https://www.grid.ac/institutes/grid.253294.b schema:alternateName Brigham Young University
359 schema:name Brigham Young University, Provo, UT, USA
360 rdf:type schema:Organization
 




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


...