基于fr切函数的位置参数非参数推断

2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO) Pub Date : 2016-02-15 DOI:10.1109/SMRLO.2016.50

V. Patrangenaru, Ruite Guo, K. D. Yao

{"title":"基于fr<s:1>切函数的位置参数非参数推断","authors":"V. Patrangenaru, Ruite Guo, K. D. Yao","doi":"10.1109/SMRLO.2016.50","DOIUrl":null,"url":null,"abstract":"Given a random object on a stratified space, one defines the Fréchet mean, the Fréchet antimean and additional population parameters associated withits Fréchet function, in case this function is a Morse function as well. In this paper we give large sample and nonparametric bootstrap estimation methods for these parameters, followed by the consistency of Fréchet sample antimean and the Central Limit Theorem of Fréchet sample antimean.","PeriodicalId":254910,"journal":{"name":"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)","volume":"162 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Nonparametric Inference for Location Parameters via Fréchet Functions\",\"authors\":\"V. Patrangenaru, Ruite Guo, K. D. Yao\",\"doi\":\"10.1109/SMRLO.2016.50\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given a random object on a stratified space, one defines the Fréchet mean, the Fréchet antimean and additional population parameters associated withits Fréchet function, in case this function is a Morse function as well. In this paper we give large sample and nonparametric bootstrap estimation methods for these parameters, followed by the consistency of Fréchet sample antimean and the Central Limit Theorem of Fréchet sample antimean.\",\"PeriodicalId\":254910,\"journal\":{\"name\":\"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)\",\"volume\":\"162 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMRLO.2016.50\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMRLO.2016.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 11

摘要

给定一个分层空间上的随机对象，我们定义了与它的frsamchet函数相关的frsamchet均值、frsamchet反均值和其他总体参数，如果这个函数也是莫尔斯函数的话。本文给出了这些参数的大样本和非参数自适应估计方法，然后给出了fr样本反均值的相合性和fr样本反均值的中心极限定理。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Nonparametric Inference for Location Parameters via Fréchet Functions

Given a random object on a stratified space, one defines the Fréchet mean, the Fréchet antimean and additional population parameters associated withits Fréchet function, in case this function is a Morse function as well. In this paper we give large sample and nonparametric bootstrap estimation methods for these parameters, followed by the consistency of Fréchet sample antimean and the Central Limit Theorem of Fréchet sample antimean.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2016 Second International Symposium on Stochastic Models in Reliability Engineering, Life Science and Operations Management (SMRLO)

自引率

0.00%

发文量