{"title":"有污染观测的独立正态序列均值变化的贝叶斯分析","authors":"Abdeldjalil Slama, H. Fellag","doi":"10.16929/AS/1779.133","DOIUrl":null,"url":null,"abstract":"In this paper, we consider a Bayesian analysis of a change in the mean of independent gaussian samples in the presence of a single outlier. An unconditional Bayesian significance test for testing change versus no change is performed under consideration of non informative prior distribution of the parameters. From a numerical study using the Gibbs sampler algorithm, the effect of a contaminated observation on the performance of the Bayesian significance test of change is studied. Keywords: Gaussian models; Change-point; HPD region sets; p-value; Outliers. AMS 2010 Mathematics Subject Classification Objects: 91B84; 62F15; 62F03","PeriodicalId":430341,"journal":{"name":"Afrika Statistika","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Bayesian analysis of a change in the mean of independent normal sequence with contaminated observation\",\"authors\":\"Abdeldjalil Slama, H. Fellag\",\"doi\":\"10.16929/AS/1779.133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we consider a Bayesian analysis of a change in the mean of independent gaussian samples in the presence of a single outlier. An unconditional Bayesian significance test for testing change versus no change is performed under consideration of non informative prior distribution of the parameters. From a numerical study using the Gibbs sampler algorithm, the effect of a contaminated observation on the performance of the Bayesian significance test of change is studied. Keywords: Gaussian models; Change-point; HPD region sets; p-value; Outliers. AMS 2010 Mathematics Subject Classification Objects: 91B84; 62F15; 62F03\",\"PeriodicalId\":430341,\"journal\":{\"name\":\"Afrika Statistika\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Afrika Statistika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.16929/AS/1779.133\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Afrika Statistika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.16929/AS/1779.133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Bayesian analysis of a change in the mean of independent normal sequence with contaminated observation
In this paper, we consider a Bayesian analysis of a change in the mean of independent gaussian samples in the presence of a single outlier. An unconditional Bayesian significance test for testing change versus no change is performed under consideration of non informative prior distribution of the parameters. From a numerical study using the Gibbs sampler algorithm, the effect of a contaminated observation on the performance of the Bayesian significance test of change is studied. Keywords: Gaussian models; Change-point; HPD region sets; p-value; Outliers. AMS 2010 Mathematics Subject Classification Objects: 91B84; 62F15; 62F03
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