{"id":196742,"identifier":"WD05DG","persistentUrl":"https://doi.org/10.18710/WD05DG","protocol":"doi","authority":"10.18710","separator":"/","publisher":"DataverseNO","publicationDate":"2024-02-22","storageIdentifier":"S3://10.18710/WD05DG","datasetType":"dataset","datasetVersion":{"id":4135,"datasetId":196742,"datasetPersistentId":"doi:10.18710/WD05DG","storageIdentifier":"S3://10.18710/WD05DG","versionNumber":1,"versionMinorNumber":0,"versionState":"RELEASED","latestVersionPublishingState":"RELEASED","deaccessionLink":"","productionDate":"2020-05-21","lastUpdateTime":"2024-02-22T13:11:17Z","releaseTime":"2024-02-22T13:11:17Z","createTime":"2024-02-14T14:06:08Z","publicationDate":"2024-02-22","citationDate":"2024-02-22","license":{"name":"CC0 1.0","uri":"http://creativecommons.org/publicdomain/zero/1.0","iconUri":"https://licensebuttons.net/p/zero/1.0/88x31.png","rightsIdentifier":"CC0-1.0","rightsIdentifierScheme":"SPDX","schemeUri":"https://spdx.org/licenses/","languageCode":"en"},"fileAccessRequest":true,"metadataBlocks":{"citation":{"displayName":"Citation Metadata","name":"citation","fields":[{"typeName":"title","multiple":false,"typeClass":"primitive","value":"A Spatial-statistical model to analyse historical rutting data"},{"typeName":"author","multiple":true,"typeClass":"compound","value":[{"authorName":{"typeName":"authorName","multiple":false,"typeClass":"primitive","value":"Jourdain, Natoya O. A. S.;  Steinsland, Ingelin; Vedvik, Emil;  Birkhez-Shami, Mamoona; Olsen, William; Gryteselv, Dagfin; Siebert, Doreen; Klein-Paste, Alex"},"authorAffiliation":{"typeName":"authorAffiliation","multiple":false,"typeClass":"primitive","value":"NTNU – Norwegian University of Science and Technology"},"authorIdentifierScheme":{"typeName":"authorIdentifierScheme","multiple":false,"typeClass":"controlledVocabulary","value":"ORCID"},"authorIdentifier":{"typeName":"authorIdentifier","multiple":false,"typeClass":"primitive","value":"https://orcid.org/0000-0001-6265-4438"}}]},{"typeName":"datasetContact","multiple":true,"typeClass":"compound","value":[{"datasetContactName":{"typeName":"datasetContactName","multiple":false,"typeClass":"primitive","value":"Jourdain, Natoya"},"datasetContactAffiliation":{"typeName":"datasetContactAffiliation","multiple":false,"typeClass":"primitive","value":"NTNU – Norwegian University of Science and Technology"},"datasetContactEmail":{"typeName":"datasetContactEmail","multiple":false,"typeClass":"primitive","value":"natoya.jourdain@ntnu.no"}}]},{"typeName":"dsDescription","multiple":true,"typeClass":"compound","value":[{"dsDescriptionValue":{"typeName":"dsDescriptionValue","multiple":false,"typeClass":"primitive","value":"The rutting dataset comprises of the annual rutting  for years 2010-2020 (millimetre, calculated as the difference between current and previous year's data), with rut depth measurement from the previous year (millimetre), annual average daily traffic (AADT), lane width (metre), bearing capacity for year 2021 (tonnes),  surface curvature index for year 2021, and base curvature index data (2021). The rutting data was collected for 20-metre road segments at specific latitude and longitude locations. The rutting is assumed to be linearly related to known explanatory variables (e.g., lane width) and random and spatial components. Rutting measurements were used to fit spatial-statistical models with random and spatial components in a Bayesian Hierarchical framework. Non spatial-statistical models with random yearly effects were also fitted. We compared these models to determine the importance of accounting for spatial information and to properly account for the rutting variability."},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2024-02-14"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Engineering","Mathematical Sciences"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Flexible pavement"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Predictive maintenance"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Rutting"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Spatial-statistical model"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Uncertainty"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Bayesian Hierarchical models"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Linear mixed models with INLA"}},{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Spatial and random effects"}}]},{"typeName":"publication","multiple":true,"typeClass":"compound","value":[{"publicationCitation":{"typeName":"publicationCitation","multiple":false,"typeClass":"primitive","value":"Jourdain N.O.A.S et al (2024) A Spatial-statistical model to analyse historical rutting data. Preprint submitted, and it will be submitted for review"},"publicationIDType":{"typeName":"publicationIDType","multiple":false,"typeClass":"controlledVocabulary","value":"arXiv"},"publicationURL":{"typeName":"publicationURL","multiple":false,"typeClass":"primitive","value":"https://doi.org/10.48550/arXiv.2401.03633"}}]},{"typeName":"producer","multiple":true,"typeClass":"compound","value":[{"producerName":{"typeName":"producerName","multiple":false,"typeClass":"primitive","value":"NTNU – Norwegian University of Science and Technology"},"producerAbbreviation":{"typeName":"producerAbbreviation","multiple":false,"typeClass":"primitive","value":"NTNU"},"producerURL":{"typeName":"producerURL","multiple":false,"typeClass":"primitive","value":"https://www.ntnu.edu/"}}]},{"typeName":"productionDate","multiple":false,"typeClass":"primitive","value":"2020-05-21"},{"typeName":"productionPlace","multiple":true,"typeClass":"primitive","value":["Trøndelag"]},{"typeName":"contributor","multiple":true,"typeClass":"compound","value":[{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Project Leader"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Andersen, Trond Michael"}},{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Data Manager"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Gryteselv, Dagfin"}},{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Project Manager"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Klein-Paste, Alex"}},{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Project Manager"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Siebert, Doreen"}},{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Supervisor"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Ingelin Steinsland"}},{"contributorType":{"typeName":"contributorType","multiple":false,"typeClass":"controlledVocabulary","value":"Researcher"},"contributorName":{"typeName":"contributorName","multiple":false,"typeClass":"primitive","value":"Jourdain, Natoya O.A.S"}}]},{"typeName":"grantNumber","multiple":true,"typeClass":"compound","value":[{"grantNumberAgency":{"typeName":"grantNumberAgency","multiple":false,"typeClass":"primitive","value":"Statens Vegvesen"},"grantNumberValue":{"typeName":"grantNumberValue","multiple":false,"typeClass":"primitive","value":"https://www.vegvesen.no/"}},{"grantNumberAgency":{"typeName":"grantNumberAgency","multiple":false,"typeClass":"primitive","value":"Norwegian University of Science and Technology"},"grantNumberValue":{"typeName":"grantNumberValue","multiple":false,"typeClass":"primitive","value":"https://www.ntnu.no/"}}]},{"typeName":"distributor","multiple":true,"typeClass":"compound","value":[{"distributorName":{"typeName":"distributorName","multiple":false,"typeClass":"primitive","value":"NTNU – Norwegian University of Science and Technology"},"distributorAbbreviation":{"typeName":"distributorAbbreviation","multiple":false,"typeClass":"primitive","value":"NTNU"},"distributorURL":{"typeName":"distributorURL","multiple":false,"typeClass":"primitive","value":"https://dataverse.no/dataverse/ntnu"}}]},{"typeName":"depositor","multiple":false,"typeClass":"primitive","value":"Jourdain, Natoya Olita Amantha Stephen"},{"typeName":"dateOfDeposit","multiple":false,"typeClass":"primitive","value":"2024-02-14"},{"typeName":"timePeriodCovered","multiple":true,"typeClass":"compound","value":[{"timePeriodCoveredStart":{"typeName":"timePeriodCoveredStart","multiple":false,"typeClass":"primitive","value":"2010-05-21"},"timePeriodCoveredEnd":{"typeName":"timePeriodCoveredEnd","multiple":false,"typeClass":"primitive","value":"2020-05-21"}}]},{"typeName":"dateOfCollection","multiple":true,"typeClass":"compound","value":[{"dateOfCollectionStart":{"typeName":"dateOfCollectionStart","multiple":false,"typeClass":"primitive","value":"2010-05-21"},"dateOfCollectionEnd":{"typeName":"dateOfCollectionEnd","multiple":false,"typeClass":"primitive","value":"2020-05-21"}}]},{"typeName":"kindOfData","multiple":true,"typeClass":"primitive","value":["Survey data"]},{"typeName":"software","multiple":true,"typeClass":"compound","value":[{"softwareName":{"typeName":"softwareName","multiple":false,"typeClass":"primitive","value":"R studio"},"softwareVersion":{"typeName":"softwareVersion","multiple":false,"typeClass":"primitive","value":"Version: 4.3.2"}},{"softwareName":{"typeName":"softwareName","multiple":false,"typeClass":"primitive","value":"INLA"},"softwareVersion":{"typeName":"softwareVersion","multiple":false,"typeClass":"primitive","value":"Version: 29-01-2024"}}]},{"typeName":"dataSources","multiple":true,"typeClass":"primitive","value":["Norwegian Public Roads Administration data bank: NVDB; Statens Vegvesen Vegkart and Rosita data base."]}]},"geospatial":{"displayName":"Geospatial Metadata","name":"geospatial","fields":[{"typeName":"geographicCoverage","multiple":true,"typeClass":"compound","value":[{"country":{"typeName":"country","multiple":false,"typeClass":"controlledVocabulary","value":"Norway"},"state":{"typeName":"state","multiple":false,"typeClass":"primitive","value":"Trøndelag"},"city":{"typeName":"city","multiple":false,"typeClass":"primitive","value":"Trondheim to Storlien on the Swedish border"}}]}]}},"files":[{"description":"Description of data","label":"00_ReadMe.txt","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":205872,"persistentId":"doi:10.18710/WD05DG/KWYWPJ","pidURL":"https://doi.org/10.18710/WD05DG/KWYWPJ","filename":"00_ReadMe.txt","contentType":"text/plain","friendlyType":"Plain Text","filesize":11329,"description":"Description of data","storageIdentifier":"S3://uit-dataverseno-prod01:18dd062be91-392a4eb18561","rootDataFileId":-1,"md5":"2fa22d1aecd1df02d832f2c0c046a17a","checksum":{"type":"MD5","value":"2fa22d1aecd1df02d832f2c0c046a17a"},"tabularData":false,"creationDate":"2024-02-22","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"All figures and plot used in preprint","label":"01_2024_Figures.zip","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":205873,"persistentId":"doi:10.18710/WD05DG/AQTRJL","pidURL":"https://doi.org/10.18710/WD05DG/AQTRJL","filename":"01_2024_Figures.zip","contentType":"application/zip","friendlyType":"ZIP Archive","filesize":13884401,"description":"All figures and plot used in preprint","storageIdentifier":"S3://uit-dataverseno-prod01:18dd06998bd-26504b8665bb","rootDataFileId":-1,"md5":"cd572537d71f1d1a1bbf134d164c959f","checksum":{"type":"MD5","value":"cd572537d71f1d1a1bbf134d164c959f"},"tabularData":false,"creationDate":"2024-02-22","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Annual rutting data, with known explanatory variables, and geographical location","label":"02_2024_Dataset.geojson","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196743,"persistentId":"doi:10.18710/WD05DG/P7XQ7V","pidURL":"https://doi.org/10.18710/WD05DG/P7XQ7V","filename":"02_2024_Dataset.geojson","contentType":"application/geo+json","friendlyType":"GeoJSON","filesize":1041458705,"description":"Annual rutting data, with known explanatory variables, and geographical location","storageIdentifier":"S3://uit-dataverseno-prod01:18da7e5354a-98dcb01191ce","rootDataFileId":-1,"md5":"a1d5e6768a5829f877f2eec6a4e0b532","checksum":{"type":"MD5","value":"a1d5e6768a5829f877f2eec6a4e0b532"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Spatial statistical rutting model with all explanatory variables (R codes)","label":"03_A_spatial_statistical_model_1_Jourdain_New_update.R","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196746,"persistentId":"doi:10.18710/WD05DG/JS4B47","pidURL":"https://doi.org/10.18710/WD05DG/JS4B47","filename":"03_A_spatial_statistical_model_1_Jourdain_New_update.R","contentType":"type/x-r-syntax","friendlyType":"R Syntax","filesize":63875,"description":"Spatial statistical rutting model with all explanatory variables (R codes)","storageIdentifier":"S3://uit-dataverseno-prod01:18da7e70343-8ea838ab6bea","rootDataFileId":-1,"md5":"6c3a71cb4468a916980dc955544fee34","checksum":{"type":"MD5","value":"6c3a71cb4468a916980dc955544fee34"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Spatial statistical rutting model with up to two explanatory variables (R codes)","label":"04_A_spatial_statistical_model_2_Jourdain_New_update.R","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196751,"persistentId":"doi:10.18710/WD05DG/GHF2CJ","pidURL":"https://doi.org/10.18710/WD05DG/GHF2CJ","filename":"04_A_spatial_statistical_model_2_Jourdain_New_update.R","contentType":"type/x-r-syntax","friendlyType":"R Syntax","filesize":62447,"description":"Spatial statistical rutting model with up to two explanatory variables (R codes)","storageIdentifier":"S3://uit-dataverseno-prod01:18da7e704da-8b084c00ef50","rootDataFileId":-1,"md5":"01909e473400fd3e58216975c7c13a75","checksum":{"type":"MD5","value":"01909e473400fd3e58216975c7c13a75"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Spatial statistical rutting model with up to one explanatory variables (R codes)","label":"05_A_spatial_statistical_model_3_Jourdain_New_update.R","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196752,"persistentId":"doi:10.18710/WD05DG/CRHMPA","pidURL":"https://doi.org/10.18710/WD05DG/CRHMPA","filename":"05_A_spatial_statistical_model_3_Jourdain_New_update.R","contentType":"type/x-r-syntax","friendlyType":"R Syntax","filesize":62497,"description":"Spatial statistical rutting model with up to one explanatory variables (R codes)","storageIdentifier":"S3://uit-dataverseno-prod01:18da7e70868-73851e140608","rootDataFileId":-1,"md5":"89a9c9795ba60cbb0b369d81e9a94e43","checksum":{"type":"MD5","value":"89a9c9795ba60cbb0b369d81e9a94e43"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Non spatial statistical rutting model with all explanatory variables (R codes)","label":"06_A_NON_spatial_statistical_model_4_Jourdain_New_update.R","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196750,"persistentId":"doi:10.18710/WD05DG/R7J5CT","pidURL":"https://doi.org/10.18710/WD05DG/R7J5CT","filename":"06_A_NON_spatial_statistical_model_4_Jourdain_New_update.R","contentType":"type/x-r-syntax","friendlyType":"R Syntax","filesize":17950,"description":"Non spatial statistical rutting model with all explanatory variables (R codes)","storageIdentifier":"S3://uit-dataverseno-prod01:18da7e714c2-493770498d65","rootDataFileId":-1,"md5":"9d33c3149461ca6bdb3a41d6e6b1c89e","checksum":{"type":"MD5","value":"9d33c3149461ca6bdb3a41d6e6b1c89e"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Non spatial statistical rutting model with up to two explanatory variables (R codes)","label":"07_A_NON_spatial_statistical_model_5_Jourdain_New_update.R","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196748,"persistentId":"doi:10.18710/WD05DG/UF67NM","pidURL":"https://doi.org/10.18710/WD05DG/UF67NM","filename":"07_A_NON_spatial_statistical_model_5_Jourdain_New_update.R","contentType":"type/x-r-syntax","friendlyType":"R Syntax","filesize":17961,"description":"Non spatial statistical rutting model with up to two explanatory variables (R codes)","storageIdentifier":"S3://uit-dataverseno-prod01:18da7e7132e-7f84249667be","rootDataFileId":-1,"md5":"09093f5b1a2160cd30ca7c060f2e5850","checksum":{"type":"MD5","value":"09093f5b1a2160cd30ca7c060f2e5850"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Non spatial statistical rutting model with up to one explanatory variables (R codes)","label":"08_A_NON_spatial_statistical_model_6_Jourdain_New_update.R","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196749,"persistentId":"doi:10.18710/WD05DG/UEYBDM","pidURL":"https://doi.org/10.18710/WD05DG/UEYBDM","filename":"08_A_NON_spatial_statistical_model_6_Jourdain_New_update.R","contentType":"type/x-r-syntax","friendlyType":"R Syntax","filesize":17080,"description":"Non spatial statistical rutting model with up to one explanatory variables (R codes)","storageIdentifier":"S3://uit-dataverseno-prod01:18da7e71116-799cc2ef7725","rootDataFileId":-1,"md5":"f2effb1a48b8305d0b8e6cdb8df6a54d","checksum":{"type":"MD5","value":"f2effb1a48b8305d0b8e6cdb8df6a54d"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Results from fitting spatial and non spatial statistical models (R codes)","label":"09_Results_from_fitting_all_models.R","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196744,"persistentId":"doi:10.18710/WD05DG/QHMIGD","pidURL":"https://doi.org/10.18710/WD05DG/QHMIGD","filename":"09_Results_from_fitting_all_models.R","contentType":"type/x-r-syntax","friendlyType":"R Syntax","filesize":238340,"description":"Results from fitting spatial and non spatial statistical models (R codes)","storageIdentifier":"S3://uit-dataverseno-prod01:18da7ed02ea-77b258656518","rootDataFileId":-1,"md5":"31065f0a4aad2a3e9cc521c9a44f3196","checksum":{"type":"MD5","value":"31065f0a4aad2a3e9cc521c9a44f3196"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Results from fitting the spatial model 1","label":"10_inlaResults_EV14_model_1.RData","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196758,"persistentId":"doi:10.18710/WD05DG/CSNOJA","pidURL":"https://doi.org/10.18710/WD05DG/CSNOJA","filename":"10_inlaResults_EV14_model_1.RData","contentType":"application/x-rlang-transport","friendlyType":"R Data","filesize":691754330,"description":"Results from fitting the spatial model 1","storageIdentifier":"S3://uit-dataverseno-prod01:18da8125480-8b3117697e4a","rootDataFileId":-1,"md5":"99d6cb1ef2fd93fc981223725a601db7","checksum":{"type":"MD5","value":"99d6cb1ef2fd93fc981223725a601db7"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Results from fitting the spatial model 2","label":"11_inlaResults_EV14_model_2.RData","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196759,"persistentId":"doi:10.18710/WD05DG/3GMBIQ","pidURL":"https://doi.org/10.18710/WD05DG/3GMBIQ","filename":"11_inlaResults_EV14_model_2.RData","contentType":"application/x-rlang-transport","friendlyType":"R Data","filesize":453191682,"description":"Results from fitting the spatial model 2","storageIdentifier":"S3://uit-dataverseno-prod01:18da8125630-2303662b8087","rootDataFileId":-1,"md5":"823bfae9993d66d09c23fd0053ed284e","checksum":{"type":"MD5","value":"823bfae9993d66d09c23fd0053ed284e"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Results from fitting the spatial model 3","label":"12_inlaResults_EV14_model_3.RData","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196760,"persistentId":"doi:10.18710/WD05DG/3VWXVL","pidURL":"https://doi.org/10.18710/WD05DG/3VWXVL","filename":"12_inlaResults_EV14_model_3.RData","contentType":"application/x-rlang-transport","friendlyType":"R Data","filesize":437458158,"description":"Results from fitting the spatial model 3","storageIdentifier":"S3://uit-dataverseno-prod01:18da8125855-ae58a01ee99d","rootDataFileId":-1,"md5":"ebe9a0e578e58247bd8ce46143adbd03","checksum":{"type":"MD5","value":"ebe9a0e578e58247bd8ce46143adbd03"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Results from fitting the non spatial model 4","label":"13_inlaResults_EV14_ns.model_4.RData","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196757,"persistentId":"doi:10.18710/WD05DG/APCJMF","pidURL":"https://doi.org/10.18710/WD05DG/APCJMF","filename":"13_inlaResults_EV14_ns.model_4.RData","contentType":"application/x-rlang-transport","friendlyType":"R Data","filesize":234059545,"description":"Results from fitting the non spatial model 4","storageIdentifier":"S3://uit-dataverseno-prod01:18da8125981-d742811b0ba3","rootDataFileId":-1,"md5":"11ecfc153b51a4b5c3162e9af7facce6","checksum":{"type":"MD5","value":"11ecfc153b51a4b5c3162e9af7facce6"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Results from fitting the non spatial model 5","label":"14_inlaResults_EV14_ns.model_5.RData","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196755,"persistentId":"doi:10.18710/WD05DG/E4ANEY","pidURL":"https://doi.org/10.18710/WD05DG/E4ANEY","filename":"14_inlaResults_EV14_ns.model_5.RData","contentType":"application/x-rlang-transport","friendlyType":"R Data","filesize":231789348,"description":"Results from fitting the non spatial model 5","storageIdentifier":"S3://uit-dataverseno-prod01:18da813e5dd-466ac4abecc8","rootDataFileId":-1,"md5":"a4ba9d047af4fdc7d858f1a488c2c3b0","checksum":{"type":"MD5","value":"a4ba9d047af4fdc7d858f1a488c2c3b0"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}},{"description":"Results from fitting the non spatial model 6","label":"15_inlaResults_EV14_ns.model_6.RData","restricted":false,"version":1,"datasetVersionId":4135,"dataFile":{"id":196756,"persistentId":"doi:10.18710/WD05DG/8LWXUK","pidURL":"https://doi.org/10.18710/WD05DG/8LWXUK","filename":"15_inlaResults_EV14_ns.model_6.RData","contentType":"application/x-rlang-transport","friendlyType":"R Data","filesize":225460482,"description":"Results from fitting the non spatial model 6","storageIdentifier":"S3://uit-dataverseno-prod01:18da81517e8-1d814998f8f9","rootDataFileId":-1,"md5":"48fe52156f8c45a44da46609d5250aa6","checksum":{"type":"MD5","value":"48fe52156f8c45a44da46609d5250aa6"},"tabularData":false,"creationDate":"2024-02-14","publicationDate":"2024-02-22","fileAccessRequest":true}}],"citation":"Jourdain, Natoya O. A. S.; Steinsland, Ingelin; Vedvik, Emil; Birkhez-Shami, Mamoona; Olsen, William; Gryteselv, Dagfin; Siebert, Doreen; Klein-Paste, Alex, 2024, \"A Spatial-statistical model to analyse historical rutting data\", https://doi.org/10.18710/WD05DG, DataverseNO, V1"}}