{"id":"https://openalex.org/W1052556267","doi":"https://doi.org/10.3233/mas-150325","title":"Robustness of marginal likelihood based tests for random regression coefficients","display_name":"Robustness of marginal likelihood based tests for random regression coefficients","publication_year":2015,"publication_date":"2015-07-20","ids":{"openalex":"https://openalex.org/W1052556267","doi":"https://doi.org/10.3233/mas-150325","mag":"1052556267"},"language":"en","primary_location":{"id":"doi:10.3233/mas-150325","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-150325","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"},"type":"article","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/A5031882088","display_name":"Maxwell L. King","orcid":null},"institutions":[{"id":"https://openalex.org/I56590836","display_name":"Monash University","ror":"https://ror.org/02bfwt286","country_code":"AU","type":"education","lineage":["https://openalex.org/I56590836"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Maxwell L. King","raw_affiliation_strings":["Monash University, Clayton, Australia","Econometrics & Business Statistics"],"affiliations":[{"raw_affiliation_string":"Monash University, Clayton, Australia","institution_ids":["https://openalex.org/I56590836"]},{"raw_affiliation_string":"Econometrics & Business Statistics","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100909817","display_name":"Shahidur Rahman","orcid":"https://orcid.org/0009-0002-4344-1992"},"institutions":[{"id":"https://openalex.org/I869467088","display_name":"KIMEP University","ror":"https://ror.org/01pk2ck74","country_code":"KZ","type":"education","lineage":["https://openalex.org/I869467088"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Shahidur Rahman","raw_affiliation_strings":["KIMEP University, Almaty, Kazakhstan","KIMEP University, Almaty, Kazakhstan,"],"affiliations":[{"raw_affiliation_string":"KIMEP University, Almaty, Kazakhstan","institution_ids":["https://openalex.org/I869467088"]},{"raw_affiliation_string":"KIMEP University, Almaty, Kazakhstan,","institution_ids":["https://openalex.org/I869467088"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5031882088"],"corresponding_institution_ids":["https://openalex.org/I56590836"],"apc_list":null,"apc_paid":null,"fwci":0.3444,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.62992207,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"10","issue":"3","first_page":"205","last_page":"220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9987000226974487,"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9987000226974487,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9983000159263611,"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/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9959999918937683,"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/statistics","display_name":"Statistics","score":0.7230068445205688},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.6463817358016968},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6134636402130127},{"id":"https://openalex.org/keywords/normality","display_name":"Normality","score":0.5678549408912659},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.550001323223114},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.5209356546401978},{"id":"https://openalex.org/keywords/score-test","display_name":"Score test","score":0.5117218494415283},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.5005865097045898},{"id":"https://openalex.org/keywords/marginal-likelihood","display_name":"Marginal likelihood","score":0.49058690667152405},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4805922210216522},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.43530458211898804},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4299643337726593},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.41363605856895447},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.2620478868484497}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.7230068445205688},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6463817358016968},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6134636402130127},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.5678549408912659},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.550001323223114},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.5209356546401978},{"id":"https://openalex.org/C103463560","wikidata":"https://www.wikidata.org/wiki/Q4456449","display_name":"Score test","level":3,"score":0.5117218494415283},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.5005865097045898},{"id":"https://openalex.org/C95923904","wikidata":"https://www.wikidata.org/wiki/Q6760420","display_name":"Marginal likelihood","level":3,"score":0.49058690667152405},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4805922210216522},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.43530458211898804},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4299643337726593},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.41363605856895447},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2620478868484497},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/mas-150325","is_oa":false,"landing_page_url":"https://doi.org/10.3233/mas-150325","pdf_url":null,"source":{"id":"https://openalex.org/S2765066696","display_name":"Model Assisted Statistics and Applications","issn_l":"1574-1699","issn":["1574-1699","1875-9068"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Model Assisted Statistics and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1967584540","https://openalex.org/W1968973014","https://openalex.org/W1971427016","https://openalex.org/W1990837693","https://openalex.org/W1997711437","https://openalex.org/W2004378206","https://openalex.org/W2008878870","https://openalex.org/W2016886155","https://openalex.org/W2028406055","https://openalex.org/W2039712062","https://openalex.org/W2048871344","https://openalex.org/W2082653250","https://openalex.org/W2084051314","https://openalex.org/W2085516189","https://openalex.org/W2088524138","https://openalex.org/W2100563906","https://openalex.org/W2108525275","https://openalex.org/W2166748222","https://openalex.org/W2527821921"],"related_works":["https://openalex.org/W1673231687","https://openalex.org/W3150222030","https://openalex.org/W2141324124","https://openalex.org/W1875078516","https://openalex.org/W2166748222","https://openalex.org/W2048669116","https://openalex.org/W4240703403","https://openalex.org/W2473791430","https://openalex.org/W2004565588","https://openalex.org/W2184984946"],"abstract_inverted_index":{"Over":[0],"the":[1,34,42,61,77,82,87,104],"last":[2],"few":[3],"decades":[4],"there":[5],"has":[6],"been":[7,20,28],"a":[8,109],"growing":[9],"literature":[10],"on":[11,23],"diagnostic":[12],"tests":[13,53,89,101],"of":[14,49,63,86],"regression":[15,58],"disturbances.":[16,66],"Tests":[17],"that":[18],"have":[19,27,103],"constructed":[21],"based":[22,52,100],"marginal":[24,50,97],"likelihood":[25,51,98],"methods":[26],"found":[29],"to":[30,74],"do":[31],"well":[32],"when":[33,54],"disturbances":[35],"are":[36,71],"normally":[37],"distributed.":[38],"This":[39],"paper":[40],"investigates":[41],"small-sample":[43],"siz":[44],"e":[45],"and":[46,81],"power":[47,84,106],"properties":[48,107],"testing":[55],"for":[56],"random":[57],"coefficients":[59],"in":[60],"presence":[62],"first-order":[64],"autoregressive":[65],"We":[67],"find":[68],"test":[69,115],"sizes":[70],"less":[72],"robust":[73],"non-normality":[75,93],"as":[76,92],"sample":[78],"size":[79],"increases":[80],"relative":[83],"performance":[85],"various":[88],"hardly":[90],"changes":[91],"is":[94],"introduced.":[95],"Consequently":[96],"score":[99],"typically":[102],"best":[105],"with":[108],"particular":[110],"approximate":[111],"point":[112],"optimal":[113],"invariant":[114],"providing":[116],"some":[117],"exceptions.":[118]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
