{“状态”:“确定”,“消息类型”:“工作”,“信息版本”:“1.0.0”,“邮件”:{“索引”:{“日期-部件”:[[2024,7,3]],“日期-时间”:“2024-07-03T19:24:03Z”,“时间戳”:1720034643160},“引用-计数”:19,“发布者”:“爱思唯尔BV”,“许可证”:[{“开始”:{-“日期-零件”:[2018,6,1]],”日期-时间“:”2018-06-01T00:00:00Z“,”timestamp“:1527811200000},”content-version“:“tdm”,“delay-in-days”:0,“URL”:“https:\/\/www.elsevier.com/tdm\/userlicense\/1.0\/”}],“资助者”:[{“DOI”:“10.13039\/501100001809”,“名称”:“中国国家自然科学基金会”,“DOI-asserted-by”:“publisher”,“奖项”:[“11671349”],“id”:[}“id”:“10.13029\/5011000001809”,”id-type“:”DOI“,”asset rted-by“:”publisher“}]}],”content-domain“:{”domain“用法:[“elsevier.com”,“sciencedirect.com”],“crossmark-restriction”:true},“short-container-title”:[“计算统计与数据分析”],”published-print“:{“date-parts”:[[2018,6]]},”DOI“:”10.1016\/j.csda.2017.10.008“,”type“:”journal-article“,”created“:”{“Data-parts“:[2017,12,23]],”date-time“:”2017-12-23T19:03:52Z“,“时间戳”:1514055832000},“第页”:“18-32”,“update-policy”:“http://\/dx.doi.org\/10.1016\/elsevier_cm_policy“,”source“:“Crossref”,“is-referenced-by-count”:18,“special_numberg”:“C”,“title”:[“Fused means \u2013特征筛选方差过滤器”],“前缀”:“10.1016”,“卷”:“122”,“作者”:[{“给定”:“晓东”,“家庭”:“燕”,“序列”:“第一”,“从属关系”:[]},{“ORCID”:“http://\/orcid.org\/00000-0001-7033-3845”,“authenticated-orcid”:false,“given”:“念生”,“family”:“唐”,“sequence”:“additional”,“affiliation”:[]},“giving”:“Jinhan”,“家人”:“谢”,“序列”:“additional”、“affidiation”:[]}“,”family“:”Wang“,”sequence“:“additional”,“affiliation”:[]}],“member”:“78”,“reference”:[{“key”:“10.1016\/j.csda.2017.10.008_b3”,“doi-asserted-by”:“crossref”,“first page”:”2123“,”doi“:”10.1214\/13-AOS1139“,”article-title“:”边际经验似然性和确定性独立性特征筛选“,”volume“:”41“,”author“:”Chang“,”year“:”2013“,”journal-title”:“Ann.Statist”},{“键”:“10.1016\/j.csda.2017.10.008_b4”,“首页”:“328”,“文章标题”:“评论”,“卷”:“86”,“作者”:“库克”,“年份”:“1991”,“日志标题”:《j.Amer.Statist.Assoc.》},{“key”:“10.116\/j.cosda.2017.1 0.008_55”,“doi-asserted-by”:“crossref”,“第一页”:”815“,“doi”:“101080\/01621459”2013.866563“,“文章标题”:“充分降维中中心子空间的融合估计量”,“volume”:“109”,“author”:“Cook”,“year”:“2014”,“journal-title”:“J.Amer.Statist.Assoc.”},{“key”:”10.1016\/J.csda.2017.10.008_b6“,”doi-asserted-by“:”crossref“,”first page“:”630“,”doi“10.1080\/01621459.2014.920256”,“article-title“:“超高维判别分析的无模型特征筛选”,“volume”:“110”,“author”:“Cui”,“year”:“2015”,“journal-title”:“J.Amer.Statist.Assoc.”},{“key”:”10.1016\/J.csda.2017.10.008_b7“,”doi-asserted-by“:”crossref“,”first page“:”544“,”doi“10.1198\/jasa.2011.tm09779”,“article-title“:“稀疏超高维可加模型中的非参数独立筛选”,“volume”:“106”,“author”:“Fan”,“year”:“2011”,“journal-title”:“J.Amer.Statist.Assoc.”},{“key”:”10.1016\/J.csda.2017.10.008_b9“,”doi-asserted-by“:”crossref“,”first page“:”849“,“doi”:“10.1111\/J.1467-9868.2008.00674.x”,“article-title“:“超高维特征空间的确定独立筛选”,“卷”:“70”,“作者”:“Fan”,“年份”:“2008”,“日志标题”:“J.R.Stat.Soc.Ser.B Stat.Methodol.”},{“键”:“10.1016\/J.csda.2017.10.008_b11”,“doi-asserted-by”:“crossref”,“首页”:“3567”,“doi”:“101214\/10-AOS798”,“article-title”:“NP维广义线性模型中的确定独立性筛选”,“卷”:“38”,“作者”:“Fan”,“年份”:“2010”,“新闻标题”:“Ann.Statist.”},{“关键”:“10.1016\/j.csda.2017.10.008_b12”,“doi-asserted-by”:“crossref”,“首页”:“81”,“doi”:“101016\/0095-0696(78)90006-2”,《文章标题》:“Hedonic价格与清洁空气需求”,“volume”:“5”,“author”:“Harrion”,“year”:“1978”,“journal-title”:“J.Environ.Econ.Manag.”},{“key”:”10.1016\/J.csda.2017.10.008_b14“,“doi-asserted-by”:“crossref”,“first page”::“342”,“doi”:“10.1214\/13-AOS1087”,“article-title“:”高维异质数据的自适应无模型变量筛选“,”volume“:”41“author:”He“,”年份“:“2013”,“journal-title”:“Ann.Statist.”},{“key”:“10.1016\/j.csda.2017.10.008_b15”,“doi-asserted-by”:“crossref”,“first-page”:“1040”,“doi”:“101214\/aos\/1176348669”,“article-title(文章标题):“切片逆回归的渐近理论”,“volument”:“20”,“author”:“Hsing”,“year”:“1992”,“journal-ttitle”:“密钥”:“10.1016\/j.csda.2017.10.008_b18”,“doi-asserted-by”:“crossref”,“first page”:“642”,“doi”:“10.1080\/01621459.2014.920257”,“article-title”:“通过动态切片的非参数k样本测试”,“volume”:”110“,“author”:“Jiang”,”year“2015”,“journal-title“:”j.Amer.Statist.Assoc.“},{”key“:”10.1016\/j.cskda.2017.1008 _b19“,”doi-asserted-by“:”crossref“,“首页”:“316”,“DOI”:“10.1080\/01621459.1991.10475035”,“article-title”:“切片逆回归降维”,“卷”:“86”,“作者”:“李”,“年份”:“1991”,“日记标题”:“J.Amer.Statist.Assoc.”},{“key”:“101016\/J.csda.2017.10.008_b20”,“DOI-asserted-by”:“crossref”,”首页“:”1846“,“DOI:”10.1016 214\/12-AOS1024“,”文章标题“:“稳健秩相关筛选”,“volume”:“40”,“author”:“Li”,“year”:“2012”,“journal-title”:“Ann.Statist.”},{“key”:”10.1016\/j.csda.2017.10.008_b21“,”doi-asserted-by“:”crossref“,”first page“:”1129“,”doi“:”10.1080\/01621459.2012.695654“,”article-title“:”通过距离相关学习进行特征筛选“,”volume“:“107”,“作者”:“李“,“year”:“2012”,“journal-title”:“J.Amer.Statist.Assoc.”},{“key”:“10.1016\/J.csda.2017.10.008_b30”,“doi-asserted-by”:“crossref”,“first-page”:“229”,“doi”:“101093\/biomet\/ass062”,“article-title“:高维二进制分类中变量筛选的Kolmogorov过滤器”,“volume”:al标题“:“Biometrika”},{“key”:“10.1016\/j.csda.2017.10.0008_b22”,“doi asserted by”:“crossref”,“首页”:“1471”,“doi”:“10.1214\/14-AOS1303”,“文章标题”:“融合kolmogorov滤波器:一种非参数无模型筛选方法”,“volume”:“43”,“author”:“Mai”,“year”:“2015”,“journal title”:“Ann.Statist.”},{“key”:“10.1016\/j.csda.2017.10.0008_b23”,“series-title”:“随机过程的收敛性”,“author”:“Pollard”,“year”:“1984”},{“key”:“10.1016\/j.csda.2017.10.008_b27”,“doi-asserted-by”:“crossref”,“first page”:”1464“,“doi”:“101198\/jasa.2011.tm10563”,“article-title”:”超高维数据的无模型特征筛选“,”volume“:”106“,”author“:”Zhu“,”year“:”2011“,“新闻标题”:“J.Amer.Statist.Assoc.”},{“key”:“10.1016\/J.csda.2017.10.008_b28”,“首页”:“727”,“文章标题”:“切片逆回归的渐近性”,“卷”:“5”,“作者”:“朱”,“年份”:“1995”,“期刊标题”:《统计》}],“容器标题”:[“计算统计与数据分析”],“原始标题”:[],“语言”:“en”,“链接”:[{“URL”:“https:\/\/api.elsevier.com/content\/article\/PII:S0167947317302566?httpAccept=text\.xml”,“content-type”:“text\/xml”,“内容-版本”:“vor”,“intended-application”:“文本-分钟”},{“URL”:“http:\/\-api.elsever.com/content\/article \/PII:S016794 731730256?httpAccess=text\/plain”离子“:”vor“,“intended-application”:“text-mining”}],“deposed”:{“date-parts”:[[2018,8,25]],“date-time”:“2018-08-25T03:35:57Z”,“timestamp”:1535168157000},“score”:1,“resource”:{primary“:{”URL“https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0167947317302566”},”副标题“:[],”短标题“[],“issued”:{“date-parts”:[[2018,6]]},“references-count”:19,“alternative-id”:[“S0167947317302566”],“URL”:“http://\/dx.doi.org\/101016\/j.csda.2017.10.008”,“relation”:{},“ISSN”:[”0167-9473“],“ISSN-type”:[{“value”:“0167-9453”,“type”:“print”}],“subject”:【】,“published”:{“date-parts”:[2018,6]]},”assertion“:【{”value“Else”vier“,”name“:”publisher“,”label“:”本文由“},{”value“维护:“Fused mean \u2013variance filter for feature screening”,“name”:“articletitle”,“label”:“Article Title”},{“value”:“Computational Statistics&Data Analysis”,“name”:“journaltitle”、“label“:”Journal Title“},}”value“:”https:\/\/doi.org\/101016\/j.csda.2017.10.008“,”name“:”articlelink“,”label“CrossRef doi link to publisher maintained version”}、,{“value”:“article”,“name”:“content_type”,“label”:“content-type”},{“value”:“\u00a9 2017 Elsevier B.V.保留所有权利。”,“名称”:“版权”,“标签”:“copyright”}]}