Mona Shokripour, A. Mohammadpour, Mina Aminghafari
{"title":"参数经验贝叶斯检验及其在小波阈值选择中的应用","authors":"Mona Shokripour, A. Mohammadpour, Mina Aminghafari","doi":"10.18869/ACADPUB.JSRI.9.2.133","DOIUrl":null,"url":null,"abstract":". In this article, we propose a new method for selecting level dependent threshold in wavelet shrinkage using the empirical Bayes framework. We employ both Bayesian and frequentist testing hypothesis instead of point estimation method. The best test yields the best prior and hence the more appropriate wavelet thresholds. The standard model functions are used to illustrate the performance of the proposed method and make comparisons with other traditional methods.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Parametric Empirical Bayes Test and Its Application to Selection of Wavelet Threshold\",\"authors\":\"Mona Shokripour, A. Mohammadpour, Mina Aminghafari\",\"doi\":\"10.18869/ACADPUB.JSRI.9.2.133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". In this article, we propose a new method for selecting level dependent threshold in wavelet shrinkage using the empirical Bayes framework. We employ both Bayesian and frequentist testing hypothesis instead of point estimation method. The best test yields the best prior and hence the more appropriate wavelet thresholds. The standard model functions are used to illustrate the performance of the proposed method and make comparisons with other traditional methods.\",\"PeriodicalId\":422124,\"journal\":{\"name\":\"Journal of Statistical Research of Iran\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistical Research of Iran\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18869/ACADPUB.JSRI.9.2.133\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Research of Iran","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18869/ACADPUB.JSRI.9.2.133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Parametric Empirical Bayes Test and Its Application to Selection of Wavelet Threshold
. In this article, we propose a new method for selecting level dependent threshold in wavelet shrinkage using the empirical Bayes framework. We employ both Bayesian and frequentist testing hypothesis instead of point estimation method. The best test yields the best prior and hence the more appropriate wavelet thresholds. The standard model functions are used to illustrate the performance of the proposed method and make comparisons with other traditional methods.