{"id":"https://openalex.org/W4416977301","doi":"https://doi.org/10.32614/rj-2025-031","title":"moonboot: An R Package Implementing m-out-of-n Bootstrap Methods","display_name":"moonboot: An R Package Implementing m-out-of-n Bootstrap Methods","publication_year":2025,"publication_date":"2025-10-24","ids":{"openalex":"https://openalex.org/W4416977301","doi":"https://doi.org/10.32614/rj-2025-031"},"language":"en","primary_location":{"id":"doi:10.32614/rj-2025-031","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2025-031","pdf_url":"https://journal.r-project.org/articles/RJ-2025-031/RJ-2025-031.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://journal.r-project.org/articles/RJ-2025-031/RJ-2025-031.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016590766","display_name":"Christoph Dalitz","orcid":"https://orcid.org/0000-0002-7004-5584"},"institutions":[{"id":"https://openalex.org/I4210113269","display_name":"Hochschule Niederrhein","ror":"https://ror.org/027b9qx26","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210113269"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christoph Dalitz","raw_affiliation_strings":["Niederrhein University of Applied Sciences"],"affiliations":[{"raw_affiliation_string":"Niederrhein University of Applied Sciences","institution_ids":["https://openalex.org/I4210113269"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5115057416","display_name":"Felix L\u00f6gler","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113269","display_name":"Hochschule Niederrhein","ror":"https://ror.org/027b9qx26","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210113269"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Felix L\u00f6gler","raw_affiliation_strings":["Niederrhein University of Applied Sciences"],"affiliations":[{"raw_affiliation_string":"Niederrhein University of Applied Sciences","institution_ids":["https://openalex.org/I4210113269"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016590766"],"corresponding_institution_ids":["https://openalex.org/I4210113269"],"apc_list":null,"apc_paid":null,"fwci":2.6124,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92717501,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"17","issue":"3","first_page":"125","last_page":"137"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13398","display_name":"Data Analysis with R","score":0.5005000233650208,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13398","display_name":"Data Analysis with R","score":0.5005000233650208,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10206","display_name":"Meta-analysis and systematic reviews","score":0.12470000237226486,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.06849999725818634,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/workaround","display_name":"Workaround","score":0.7202000021934509},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6028000116348267},{"id":"https://openalex.org/keywords/r-package","display_name":"R package","score":0.5788999795913696},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5759999752044678},{"id":"https://openalex.org/keywords/confidence-interval","display_name":"Confidence interval","score":0.5072000026702881},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.4578999876976013},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.32420000433921814},{"id":"https://openalex.org/keywords/confidence-distribution","display_name":"Confidence distribution","score":0.3109999895095825}],"concepts":[{"id":"https://openalex.org/C194541083","wikidata":"https://www.wikidata.org/wiki/Q457174","display_name":"Workaround","level":2,"score":0.7202000021934509},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6028000116348267},{"id":"https://openalex.org/C2984074130","wikidata":"https://www.wikidata.org/wiki/Q73539779","display_name":"R package","level":2,"score":0.5788999795913696},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5759999752044678},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5565000176429749},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5072000026702881},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4090000092983246},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39309999346733093},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37040001153945923},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.32420000433921814},{"id":"https://openalex.org/C13662513","wikidata":"https://www.wikidata.org/wiki/Q5160087","display_name":"Confidence distribution","level":3,"score":0.3109999895095825},{"id":"https://openalex.org/C143380155","wikidata":"https://www.wikidata.org/wiki/Q5160088","display_name":"Confidence region","level":3,"score":0.304500013589859},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C2777205145","wikidata":"https://www.wikidata.org/wiki/Q4944080","display_name":"Bootstrap model","level":4,"score":0.28439998626708984},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2694000005722046},{"id":"https://openalex.org/C6239989","wikidata":"https://www.wikidata.org/wiki/Q5419224","display_name":"Exact statistics","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C66520545","wikidata":"https://www.wikidata.org/wiki/Q7353538","display_name":"Robust confidence intervals","level":3,"score":0.2615000009536743},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25679999589920044},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C2776292839","wikidata":"https://www.wikidata.org/wiki/Q5179217","display_name":"Coverage probability","level":3,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32614/rj-2025-031","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2025-031","pdf_url":"https://journal.r-project.org/articles/RJ-2025-031/RJ-2025-031.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32614/rj-2025-031","is_oa":true,"landing_page_url":"https://doi.org/10.32614/rj-2025-031","pdf_url":"https://journal.r-project.org/articles/RJ-2025-031/RJ-2025-031.pdf","source":{"id":"https://openalex.org/S2489169438","display_name":"The R Journal","issn_l":"2073-4859","issn":["2073-4859"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The R Journal","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416977301.pdf","grobid_xml":"https://content.openalex.org/works/W4416977301.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"m-out-of-n":[1,66],"bootstrap":[2,12,67],"is":[3],"a":[4],"possible":[5],"workaround":[6],"to":[7],"compute":[8],"confidence":[9,68],"intervals":[10,69],"for":[11,45,73,94],"inconsistent":[13],"estimators,":[14],"because":[15],"it":[16,31],"works":[17],"under":[18],"weaker":[19],"conditions":[20],"than":[21],"the":[22,27,42,50,63,75,88],"n-out-of-n":[23],"bootstrap.":[24],"It":[25],"has":[26],"disadvantage,":[28],"however,":[29],"that":[30,41],"requires":[32],"knowledge":[33],"of":[34,52,65,82],"an":[35,57],"appropriate":[36],"scaling":[37],"factor":[38],"tau(n)":[39,77],"and":[40,70,78,91],"coverage":[43],"probability":[44],"finite":[46],"n":[47],"depends":[48],"on":[49],"choice":[51],"m.":[53,79],"This":[54],"article":[55],"presents":[56],"R":[58],"package":[59],"moonboot":[60],"which":[61],"implements":[62],"computation":[64],"provides":[71],"functions":[72],"estimating":[74],"parameters":[76],"By":[80],"means":[81],"Monte":[83],"Carlo":[84],"simulations,":[85],"we":[86],"evaluate":[87],"different":[89,95],"methods":[90],"compare":[92],"them":[93],"estimators.":[96]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-12-04T00:00:00"}
