{"id":"https://openalex.org/W4243815799","doi":"https://doi.org/10.1002/9781119675860.ch6","title":"Parameter Estimation","display_name":"Parameter Estimation","publication_year":2020,"publication_date":"2020-08-10","ids":{"openalex":"https://openalex.org/W4243815799","doi":"https://doi.org/10.1002/9781119675860.ch6"},"language":"ca","primary_location":{"id":"doi:10.1002/9781119675860.ch6","doi":"https://doi.org/10.1002/9781119675860.ch6","is_oa":false,"landing_page_url":"https://doi.org/10.1002/9781119675860.ch6","pdf_url":null,"source":{"id":"https://openalex.org/S73550732","display_name":"Statistics","issn_l":"0233-1888","issn":["0233-1888","1026-7786","1029-4910"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","dongbi-d","doyens","jufo-1","norway-1","poland-70","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics","raw_type":"other"},"volume":{"id":"https://openalex.org/W3049471129","display_name":"Statistics"},"type":"book-chapter","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109809512","display_name":"David W. Scott","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David W. Scott","raw_affiliation_strings":["Rice University, Houston, Texas"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rice University, Houston, Texas","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5109809512"],"corresponding_institution_ids":["https://openalex.org/I74775410"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"79","last_page":"92"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.923799991607666,"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"}},"topics":[{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.923799991607666,"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"}},{"id":"https://openalex.org/T13500","display_name":"Probability and Statistical Research","score":0.05640000104904175,"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"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.00559999980032444,"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/parameter-estimation","display_name":"parameter estimation","score":0.5960000157356262},{"id":"https://openalex.org/keywords/sample-mean","display_name":"sample mean","score":0.6779999732971191},{"id":"https://openalex.org/keywords/sampling-distribution","display_name":"sampling distribution","score":0.7210000157356262},{"id":"https://openalex.org/keywords/method-of-moments","display_name":"method of moments","score":0.7879999876022339},{"id":"https://openalex.org/keywords/sufficient-statistics","display_name":"sufficient statistics","score":0.9629999995231628},{"id":"https://openalex.org/keywords/data-compression","display_name":"data compression","score":0.9300000071525574},{"id":"https://openalex.org/keywords/bayesian-parameter-estimation","display_name":"Bayesian parameter estimation","score":0.9399999976158142},{"id":"https://openalex.org/keywords/maximum-likelihood-estimation","display_name":"maximum likelihood estimation","score":0.9190000295639038},{"id":"https://openalex.org/keywords/likelihood-function","display_name":"likelihood function","score":0.8190000057220459}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6872317790985107},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.589128315448761},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5761361122131348},{"id":"https://openalex.org/C162376815","wikidata":"https://www.wikidata.org/wiki/Q2158281","display_name":"Frequentist inference","level":4,"score":0.5642330646514893},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.5376383662223816},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44409313797950745},{"id":"https://openalex.org/C189508267","wikidata":"https://www.wikidata.org/wiki/Q17088227","display_name":"Density estimation","level":3,"score":0.43891555070877075},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4301181435585022},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.37333929538726807},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.1851063370704651}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/9781119675860.ch6","doi":"https://doi.org/10.1002/9781119675860.ch6","is_oa":false,"landing_page_url":"https://doi.org/10.1002/9781119675860.ch6","pdf_url":null,"source":{"id":"https://openalex.org/S73550732","display_name":"Statistics","issn_l":"0233-1888","issn":["0233-1888","1026-7786","1029-4910"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-class-a","anvur-scientific","cwts-core","dongbi-d","doyens","jufo-1","norway-1","poland-70","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Statistics","raw_type":"other"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3123759439","https://openalex.org/W4388395554","https://openalex.org/W4400123514","https://openalex.org/W3111106947","https://openalex.org/W2767629477","https://openalex.org/W4410420954","https://openalex.org/W3111782713","https://openalex.org/W3150875183","https://openalex.org/W3014200381","https://openalex.org/W2181458293"],"abstract_inverted_index":{"This":[0],"chapter":[1,54,79],"focuses":[2,56],"on":[3,57],"parametric":[4],"probability":[5,23],"density":[6,24],"estimation,":[7],"assuming":[8],"the":[9,18,22,36,40,51,53,60,68,75,81,92,97,120,126],"statistician":[10,117],"or":[11],"subject":[12],"matter":[13],"expert":[14],"has":[15],"correctly":[16],"selected":[17],"appropriate":[19],"choice":[20],"for":[21],"function":[25,49],"(PDF).":[26],"An":[27],"estimator":[28],"of":[29,42,50,59,74,96,103],"a":[30,33,43,48],"parameter":[31,112],"is":[32],"formula":[34],"using":[35],"random":[37,87],"sample.":[38],"Since":[39],"moments":[41],"PDF":[44],"will":[45],"generally":[46],"be":[47],"parameters,":[52],"also":[55],"estimators":[58],"first":[61],"two":[62],"moments.":[63],"It":[64,100],"begins":[65],"by":[66],"computing":[67],"theoretical":[69,72],"mean":[70,93],"and":[71,94,107,110],"variance":[73,95],"sample":[76],"mean.":[77],"The":[78,114],"helps":[80],"reader":[82],"to":[83,91],"learn":[84],"how":[85],"these":[86],"variables":[88],"are":[89],"related":[90],"sampling":[98],"density.":[99],"discusses":[101],"method":[102],"moments,":[104],"sufficient":[105],"statistics":[106],"data":[108],"compression,":[109],"Bayesian":[111],"estimation.":[113],"frequentist":[115],"(non-Bayesian)":[116],"usually":[118],"chooses":[119],"maximum":[121],"likelihood":[122,127],"estimator,":[123],"which":[124],"maximizes":[125],"function.":[128]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2022-05-12T00:00:00"}
