{"id":"https://openalex.org/W3195842615","doi":"https://doi.org/10.3390/computation9090094","title":"EM Estimation for Zero- and k-Inflated Poisson Regression Model","display_name":"EM Estimation for Zero- and k-Inflated Poisson Regression Model","publication_year":2021,"publication_date":"2021-08-26","ids":{"openalex":"https://openalex.org/W3195842615","doi":"https://doi.org/10.3390/computation9090094","mag":"3195842615"},"language":"en","primary_location":{"id":"doi:10.3390/computation9090094","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computation9090094","pdf_url":"https://www.mdpi.com/2079-3197/9/9/94/pdf?version=1630057857","source":{"id":"https://openalex.org/S2738402919","display_name":"Computation","issn_l":"2079-3197","issn":["2079-3197"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2079-3197/9/9/94/pdf?version=1630057857","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101902470","display_name":"Monika Arora","orcid":"https://orcid.org/0000-0003-4507-9405"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Monika Arora","raw_affiliation_strings":["Department of Mathematics, Indraprastha Institute of Information Technology, Delhi 110020, India"],"raw_orcid":"https://orcid.org/0000-0003-4507-9405","affiliations":[{"raw_affiliation_string":"Department of Mathematics, Indraprastha Institute of Information Technology, Delhi 110020, India","institution_ids":["https://openalex.org/I119939252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076594483","display_name":"N. Rao Chaganty","orcid":"https://orcid.org/0000-0003-2325-3513"},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"N. Rao Chaganty","raw_affiliation_strings":["Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA 23529-0077, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA 23529-0077, USA","institution_ids":["https://openalex.org/I81365321"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076594483"],"corresponding_institution_ids":["https://openalex.org/I81365321"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":1.4998,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84369352,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":"9","first_page":"94","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9990000128746033,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9990000128746033,"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/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9822999835014343,"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/zero-inflated-model","display_name":"Zero-inflated model","score":0.7837589979171753},{"id":"https://openalex.org/keywords/count-data","display_name":"Count data","score":0.7755115032196045},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.7707303166389465},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6857669949531555},{"id":"https://openalex.org/keywords/poisson-regression","display_name":"Poisson regression","score":0.6472910642623901},{"id":"https://openalex.org/keywords/zero","display_name":"Zero (linguistics)","score":0.6179132461547852},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.5904065370559692},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5782995820045471},{"id":"https://openalex.org/keywords/compound-poisson-distribution","display_name":"Compound Poisson distribution","score":0.5057961940765381},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4775429666042328},{"id":"https://openalex.org/keywords/quasi-likelihood","display_name":"Quasi-likelihood","score":0.4730460047721863},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42543086409568787},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.41498127579689026},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.2093656361103058},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.1353088915348053}],"concepts":[{"id":"https://openalex.org/C88721176","wikidata":"https://www.wikidata.org/wiki/Q966010","display_name":"Zero-inflated model","level":4,"score":0.7837589979171753},{"id":"https://openalex.org/C33643355","wikidata":"https://www.wikidata.org/wiki/Q5176731","display_name":"Count data","level":3,"score":0.7755115032196045},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.7707303166389465},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6857669949531555},{"id":"https://openalex.org/C73269764","wikidata":"https://www.wikidata.org/wiki/Q954529","display_name":"Poisson regression","level":3,"score":0.6472910642623901},{"id":"https://openalex.org/C2780813799","wikidata":"https://www.wikidata.org/wiki/Q3274237","display_name":"Zero (linguistics)","level":2,"score":0.6179132461547852},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.5904065370559692},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5782995820045471},{"id":"https://openalex.org/C178174526","wikidata":"https://www.wikidata.org/wiki/Q3711786","display_name":"Compound Poisson distribution","level":4,"score":0.5057961940765381},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4775429666042328},{"id":"https://openalex.org/C91025261","wikidata":"https://www.wikidata.org/wiki/Q7269460","display_name":"Quasi-likelihood","level":4,"score":0.4730460047721863},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42543086409568787},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.41498127579689026},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2093656361103058},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.1353088915348053},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/computation9090094","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computation9090094","pdf_url":"https://www.mdpi.com/2079-3197/9/9/94/pdf?version=1630057857","source":{"id":"https://openalex.org/S2738402919","display_name":"Computation","issn_l":"2079-3197","issn":["2079-3197"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computation","raw_type":"journal-article"},{"id":"pmh:oai:digitalcommons.odu.edu:mathstat_fac_pubs-1191","is_oa":true,"landing_page_url":"https://digitalcommons.odu.edu/mathstat_fac_pubs/191","pdf_url":null,"source":{"id":"https://openalex.org/S4377196314","display_name":"ODU Digital Commons (Old Dominion University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I81365321","host_organization_name":"Old Dominion University","host_organization_lineage":["https://openalex.org/I81365321"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Mathematics & Statistics Faculty Publications","raw_type":"article"},{"id":"pmh:oai:doaj.org/article:1c3ce5044e1643768ad8a5e62c0e7c1f","is_oa":true,"landing_page_url":"https://doaj.org/article/1c3ce5044e1643768ad8a5e62c0e7c1f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computation, Vol 9, Iss 9, p 94 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2079-3197/9/9/94/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/computation9090094","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computation; Volume 9; Issue 9; Pages: 94","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/computation9090094","is_oa":true,"landing_page_url":"https://doi.org/10.3390/computation9090094","pdf_url":"https://www.mdpi.com/2079-3197/9/9/94/pdf?version=1630057857","source":{"id":"https://openalex.org/S2738402919","display_name":"Computation","issn_l":"2079-3197","issn":["2079-3197"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computation","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3195842615.pdf","grobid_xml":"https://content.openalex.org/works/W3195842615.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W109690219","https://openalex.org/W1867645765","https://openalex.org/W1876871846","https://openalex.org/W1964355708","https://openalex.org/W1973628995","https://openalex.org/W1993189875","https://openalex.org/W2004168513","https://openalex.org/W2024764857","https://openalex.org/W2029761439","https://openalex.org/W2031144387","https://openalex.org/W2036331394","https://openalex.org/W2047828157","https://openalex.org/W2049633694","https://openalex.org/W2060817938","https://openalex.org/W2077724217","https://openalex.org/W2079075343","https://openalex.org/W2081647076","https://openalex.org/W2082178566","https://openalex.org/W2089905787","https://openalex.org/W2100085382","https://openalex.org/W2102810005","https://openalex.org/W2118606895","https://openalex.org/W2119634512","https://openalex.org/W2125961882","https://openalex.org/W2142635246","https://openalex.org/W2154425398","https://openalex.org/W2264769597","https://openalex.org/W2593096752","https://openalex.org/W2596975326","https://openalex.org/W2620902034","https://openalex.org/W2770161301","https://openalex.org/W2912561960","https://openalex.org/W2948959699","https://openalex.org/W2954856762","https://openalex.org/W2955183493","https://openalex.org/W2980337364","https://openalex.org/W3124757284","https://openalex.org/W3126100411","https://openalex.org/W3189805653","https://openalex.org/W6604700077","https://openalex.org/W6639436193","https://openalex.org/W6693196769","https://openalex.org/W6734141969","https://openalex.org/W6763482479"],"related_works":["https://openalex.org/W2901798679","https://openalex.org/W3120214361","https://openalex.org/W2043122071","https://openalex.org/W2060931646","https://openalex.org/W2116405300","https://openalex.org/W2138071539","https://openalex.org/W4205626288","https://openalex.org/W1586083680","https://openalex.org/W2011515496","https://openalex.org/W1576579675"],"abstract_inverted_index":{"Count":[0],"data":[1,134,144],"with":[2],"excessive":[3,30],"zeros":[4],"are":[5,14],"ubiquitous":[6],"in":[7,33,48,61,149],"healthcare,":[8],"medical,":[9],"and":[10,23,53,74,80,132],"scientific":[11],"studies.":[12],"There":[13],"numerous":[15],"articles":[16],"that":[17],"show":[18],"how":[19],"to":[20,45],"fit":[21],"Poisson":[22,55,73],"other":[24],"models":[25],"which":[26],"account":[27],"for":[28,100,114],"the":[29,38,49,87,105,110,120,124,129,139,146,150],"zeros.":[31],"However,":[32],"many":[34],"situations,":[35],"besides":[36],"zero,":[37],"frequency":[39],"of":[40,72,90,104,123,141],"another":[41],"count":[42],"k":[43],"tends":[44],"be":[46],"higher":[47],"data.":[50,117],"The":[51,64],"zero-":[52],"k-inflated":[54],"distribution":[56,66,71],"model":[57,108],"(ZkIP)":[58],"is":[59,68],"appropriate":[60],"such":[62],"situations":[63],"ZkIP":[65,106],"essentially":[67],"a":[69,115],"mixture":[70,92],"degenerate":[75],"distributions":[76],"at":[77],"points":[78],"zero":[79],"k.":[81],"In":[82],"this":[83,91],"article,":[84],"we":[85,97],"study":[86],"fundamental":[88],"properties":[89],"distribution.":[93],"Using":[94],"stochastic":[95],"representation,":[96],"provide":[98],"details":[99],"obtaining":[101],"parameter":[102],"estimates":[103,126],"regression":[107],"using":[109,145],"Expectation\u2013Maximization":[111],"(EM)":[112],"algorithm":[113],"given":[116],"We":[118,137],"derive":[119],"standard":[121],"errors":[122],"EM":[125],"by":[127],"computing":[128],"complete,":[130],"missing,":[131],"observed":[133],"information":[135],"matrices.":[136],"present":[138],"analysis":[140],"two":[142],"real-life":[143],"methods":[147],"outlined":[148],"paper.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2021-08-30T00:00:00"}