[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_221":222},"routes/_layout",{"_11":132},"routes/entity.$type.$id",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":19,"_20":21,"_22":23,"_24":-7,"_25":26},"dehydratedState",{"_58":59,"_60":61},"type","person","id","person_A5083701620","section","entity",{"_15":16,"_27":28,"_29":-5,"_30":-5,"_31":-5,"_32":-5,"_33":34,"_35":36,"_37":-5,"_38":39,"_40":41,"_42":43,"_44":45,"_46":-5,"_47":-5,"_48":-5,"_49":-5,"_50":-5,"_51":-5,"_52":-5,"_53":-5,"_54":-5,"_55":-5,"_56":28,"_57":-5},"canonical","https://www.hugmap.com/entity/person/person_A5083701620","siteBaseUrl","https://www.hugmap.com","sectionCount","jsonLd","{\"@context\":\"https://schema.org\",\"@graph\":[{\"name\":\"Ingmar Visser\",\"url\":\"https://www.hugmap.com/entity/person/person_A5083701620\",\"@type\":\"Person\",\"jobTitle\":null},{\"@type\":\"BreadcrumbList\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"首页\",\"item\":\"https://www.hugmap.com/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"人物\",\"item\":\"https://www.hugmap.com/search?type=person\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"Ingmar Visser\",\"item\":\"https://www.hugmap.com/entity/person/person_A5083701620\"}]}]}","name","Ingmar Visser","nameZh","aliases","description","descriptionZh","status","active","externalIds","{\"openalex\":\"A5083701620\",\"orcid\":\"0000-0003-3855-2778\"}","properties","source","openalex","createdAt","2026-05-19T13:51:10.177031648","updatedAt","2026-05-19T13:51:10.177091614","orcid","0000-0003-3855-2778","title","affiliation","researchArea","paperCount","citationCount","homepage","linkedin","twitter","github","hindex","displayName","displayDescription","mutations",[],"queries",[62],{"_63":64,"_65":66,"_67":68,"_69":70},"dehydratedAt",1780536445229,"state",{"_72":73,"_74":75,"_76":64,"_77":-5,"_78":79,"_80":79,"_81":79,"_82":-5,"_83":-5,"_84":85,"_33":86,"_87":88},"queryKey",[71,18,14,16],"queryHash","[\"portal\",\"entity\",\"person\",\"person_A5083701620\"]","portal","data",{"_18":19,"_89":90,"_91":92,"_93":94,"_95":96,"_97":98,"_99":100,"_101":102},"dataUpdateCount",1,"dataUpdatedAt","error","errorUpdateCount",0,"errorUpdatedAt","fetchFailureCount","fetchFailureReason","fetchMeta","isInvalidated",false,"success","fetchStatus","idle","entityType","Person","taxonomies",[],"papers",[103],"companies",[],"events",[],"patents",[],"articles",[],{"_15":104,"_27":105,"_29":-5,"_30":-5,"_31":-5,"_32":-5,"_33":34,"_35":106,"_37":-5,"_38":39,"_40":107,"_42":108,"_109":110,"_111":-5,"_112":113,"_46":105,"_114":115,"_116":117,"_118":119,"_120":121,"_50":122,"_123":-5,"_124":125,"_126":-5,"_127":128,"_56":105,"_57":-5},"paper_W2152315455","depmixS4: AnRPackage for Hidden Markov Models","{\"openalex\":\"W2152315455\",\"doi\":\"10.18637/jss.v036.i07\"}","2026-05-19T13:51:09.237029804","2026-05-19T13:51:09.23746535","doi","10.18637/jss.v036.i07","arxivId","openalexId","W2152315455","abstractText","depmixS4 implements a general framework for defining and estimating dependent mixture models in the R programming language. This includes standard Markov models, latent/hidden Markov models, and latent class and finite mixture distribution models. The models can be fitted on mixed multivariate data with distributions from the glm family, the (logistic) multinomial, or the multivariate normal distribution. Other distributions can be added easily, and an example is provided with the exgaus distribution. Parameters are estimated by the expectation-maximization (EM) algorithm or, when (linear) constraints are imposed on the parameters, by direct numerical optimization with the Rsolnp or Rdonlp2 routines.","publishedDate","2010-01-01","publishedYear",2010,"venue","Journal of Statistical Software",407,"authors","keywords",[129,130,131],"pdfUrl","topVenue",true,"Bayesian Methods and Mixture Models","Statistical Methods and Bayesian Inference","Bayesian Modeling and Causal Inference",{"_58":133,"_60":134},[],[135],{"_63":136,"_65":137,"_67":138,"_69":139},1780536443211,{"_72":141,"_74":75,"_76":136,"_77":-5,"_78":79,"_80":79,"_81":79,"_82":-5,"_83":-5,"_84":85,"_33":86,"_87":88},[71,140],"[\"portal\",\"industries\"]","industries",[142,143,144,145,146,147,148,149,150,151,152,153],{"_15":214,"_27":215,"_29":-5,"_30":216,"_31":217,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":218,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":215,"_57":217},{"_15":210,"_27":211,"_29":-5,"_30":-5,"_31":212,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":213,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":211,"_57":212},{"_15":204,"_27":205,"_29":-5,"_30":206,"_31":207,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":208,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":205,"_57":207},{"_15":200,"_27":201,"_29":-5,"_30":-5,"_31":202,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":203,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":201,"_57":202},{"_15":196,"_27":197,"_29":-5,"_30":-5,"_31":198,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":199,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":197,"_57":198},{"_15":190,"_27":191,"_29":-5,"_30":192,"_31":193,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":194,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":191,"_57":193},{"_15":186,"_27":187,"_29":-5,"_30":-5,"_31":188,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":189,"_166":79,"_167":128,"_168":79,"_169":-5,"_56":187,"_57":188},{"_15":182,"_27":183,"_29":-5,"_30":-5,"_31":184,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":185,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":183,"_57":184},{"_15":178,"_27":179,"_29":-5,"_30":-5,"_31":180,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":181,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":179,"_57":180},{"_15":174,"_27":175,"_29":-5,"_30":-5,"_31":176,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":177,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":175,"_57":176},{"_15":170,"_27":171,"_29":-5,"_30":-5,"_31":172,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":173,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":171,"_57":172},{"_15":154,"_27":155,"_29":-5,"_30":-5,"_31":156,"_32":-5,"_33":34,"_35":-5,"_37":-5,"_38":157,"_40":-5,"_42":-5,"_158":159,"_160":-5,"_161":75,"_162":163,"_164":165,"_166":79,"_167":85,"_168":79,"_169":-5,"_56":155,"_57":156},"tax_ind_smartphone","智能手机","Smartphone","manual","taxonomyType","INDUSTRY","code","level","parentId","tax_ind_root","path","科技行业/智能手机","sortOrder","isLeaf","entityCount","children","tax_ind_robot","机器人","Robotics","科技行业/机器人","tax_ind_wearable","智能穿戴","Smart Wearables","科技行业/智能穿戴","tax_ind_energy","新能源与智能制造","New Energy & Smart Manufacturing","科技行业/新能源与智能制造","tax_ind_biotech","生物科技","Biotech","科技行业/生物科技","tax_ind_quantum","量子计算","Quantum Computing","科技行业/量子计算","tax_ind_blockchain","区块链",[195],"Blockchain","科技行业/区块链","Web3","tax_ind_enterprise","企业软件","Enterprise Software","科技行业/企业软件","tax_ind_security","网络安全","Cybersecurity","科技行业/网络安全","tax_ind_semi","半导体",[209],"Semiconductor","科技行业/半导体","芯片","tax_ind_cloud","云计算","Cloud Computing","科技行业/云计算","tax_ind_ai","人工智能",[219,220],"Artificial Intelligence","科技行业/人工智能","AI","AI 技术","env",{"_223":23},"SITE_BASE_URL"]

Ingmar Visser 人物

相关论文查看全部 (1)

相关公司

相关事件

相关专利

相关文章