{"id":"https://openalex.org/W154650571","doi":null,"title":"Problems in Model Averaging with Dummy Variables","display_name":"Problems in Model Averaging with Dummy Variables","publication_year":2005,"publication_date":"2005-01-01","ids":{"openalex":"https://openalex.org/W154650571","mag":"154650571"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.473.2245","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.473.2245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://folk.uio.no/rnymoen/Evalwork_ModAver.pdf","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5014898803","display_name":"David Forbes Hendry","orcid":"https://orcid.org/0000-0002-8013-576X","observed_orcids":["https://orcid.org/0000-0002-8013-576X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David F. Hendry","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5083232109","display_name":"J. James Reade","orcid":"https://orcid.org/0000-0002-8610-530X","observed_orcids":["https://orcid.org/0000-0002-8610-530X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"J. James Reade","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9712,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.74980127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.8842999935150146,"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/T10136","display_name":"Statistical Methods and Inference","score":0.8842999935150146,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.054099999368190765,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/T11871","display_name":"Advanced Statistical Methods and Models","score":0.013799999840557575,"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/model-averaging","display_name":"model averaging","score":1.0},{"id":"https://openalex.org/keywords/dummy-variables","display_name":"dummy variables","score":0.9210000038146973},{"id":"https://openalex.org/keywords/model-uncertainty","display_name":"model uncertainty","score":0.9660000205039978},{"id":"https://openalex.org/keywords/coefficient-bias","display_name":"coefficient bias","score":0.6629999876022339},{"id":"https://openalex.org/keywords/forecast-error","display_name":"forecast error","score":0.9589999914169312},{"id":"https://openalex.org/keywords/outliers","display_name":"outliers","score":0.9729999899864197},{"id":"https://openalex.org/keywords/structural-breaks","display_name":"structural breaks","score":1.0},{"id":"https://openalex.org/keywords/model-selection","display_name":"model selection","score":0.7229999899864197},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.5720000267028809},{"id":"https://openalex.org/keywords/monte-carlo-simulation","display_name":"Monte Carlo simulation","score":0.5740000009536743}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7481323480606079},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.6494084000587463},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.5862540602684021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5705278515815735},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5591055154800415},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.519437313079834},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5129908919334412},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.463911235332489},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4321516156196594},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.306938111782074},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3013949990272522},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29894888401031494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24724015593528748},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08469340205192566},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.473.2245","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.473.2245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://folk.uio.no/rnymoen/Evalwork_ModAver.pdf","raw_type":"text"},{"id":"mag:154650571","doi":null,"is_oa":false,"landing_page_url":"http://folk.uio.no/rnymoen/Evalwork_ModAver.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1586773673","https://openalex.org/W1800261609","https://openalex.org/W1913804012","https://openalex.org/W1983936468","https://openalex.org/W1994672023","https://openalex.org/W2098418171","https://openalex.org/W2100819337","https://openalex.org/W2117780630","https://openalex.org/W2121286295","https://openalex.org/W2135728169","https://openalex.org/W2164141257","https://openalex.org/W2164821349","https://openalex.org/W2337584682","https://openalex.org/W3021526567","https://openalex.org/W3121565678","https://openalex.org/W3122123604","https://openalex.org/W3124636723"],"related_works":["https://openalex.org/W1866077154","https://openalex.org/W1981295458","https://openalex.org/W2624721943","https://openalex.org/W614841257","https://openalex.org/W4229849994","https://openalex.org/W2116356927","https://openalex.org/W1980370194","https://openalex.org/W7099364963","https://openalex.org/W7098187151","https://openalex.org/W1572250146"],"abstract_inverted_index":{"Model":[0],"averaging":[1,27],"is":[2,72,82,111],"widely":[3],"used":[4],"in":[5,30,48,61],"empirical":[6,23],"work,":[7],"and":[8,36,44,56],"proposed":[9],"as":[10],"a":[11,19],"solution":[12],"to":[13,91,98],"model":[14,26,108],"uncertainty.":[15],"This":[16],"paper":[17],"provides":[18],"range":[20],"of":[21,32,86,107],"relevant":[22,77],"contexts":[24,40],"where":[25],"performs":[28],"poorly":[29],"terms":[31],"bias":[33,95],"on":[34],"coefficients":[35],"forecast":[37],"errors.":[38],"These":[39],"are":[41],"when":[42],"outliers":[43],"structural":[45],"breaks":[46],"exist":[47],"datasets.":[49],"Monte":[50],"Carlo":[51],"simulations":[52],"support":[53],"these":[54],"assertions":[55],"suggest":[57],"that":[58,74,96],"they":[59],"apply":[60],"more":[62],"complicated":[63],"models":[64],"than":[65],"the":[66,84,99,104],"simple":[67],"ones":[68,81],"considered":[69],"here.":[70],"It":[71],"argued":[73],"not":[75],"selecting":[76],"variables":[78],"over":[79],"irrelevant":[80,92],"precisely":[83],"cause":[85],"poor":[87],"performance;":[88],"weights":[89],"ascribed":[90],"components":[93],"will":[94],"attributable":[97],"relevant.":[100],"Within":[101],"this":[102],"context,":[103],"superior":[105],"performance":[106],"selection":[109],"algorithms":[110],"indicated.":[112],"1":[113]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}
