{"title":"基于2×2列联表的非参数与参数推理","authors":"P. Sulewski","doi":"10.12921/cmst.2018.0000009","DOIUrl":null,"url":null,"abstract":"This paper proposes scenarios of generating contingency tables (CTs) with the probability flow parameter (PFP). It also defines measures of untruthfulness of H0 that involve PFP for all proposed scenarios. This paper is an attempt to replace a nonparametric statistical inference method by the parametric one. The paper applies the maximum likelihood method to estimate PFP and presents instructions to generate CTs by means of the bar method. The Monte Carlo method is used to carry out computer simulations.","PeriodicalId":10561,"journal":{"name":"computational methods in science and technology","volume":"40 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nonparametric Versus Parametric Reasoning Based on 2×2 Contingency Tables\",\"authors\":\"P. Sulewski\",\"doi\":\"10.12921/cmst.2018.0000009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes scenarios of generating contingency tables (CTs) with the probability flow parameter (PFP). It also defines measures of untruthfulness of H0 that involve PFP for all proposed scenarios. This paper is an attempt to replace a nonparametric statistical inference method by the parametric one. The paper applies the maximum likelihood method to estimate PFP and presents instructions to generate CTs by means of the bar method. The Monte Carlo method is used to carry out computer simulations.\",\"PeriodicalId\":10561,\"journal\":{\"name\":\"computational methods in science and technology\",\"volume\":\"40 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"computational methods in science and technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12921/cmst.2018.0000009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"computational methods in science and technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12921/cmst.2018.0000009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nonparametric Versus Parametric Reasoning Based on 2×2 Contingency Tables
This paper proposes scenarios of generating contingency tables (CTs) with the probability flow parameter (PFP). It also defines measures of untruthfulness of H0 that involve PFP for all proposed scenarios. This paper is an attempt to replace a nonparametric statistical inference method by the parametric one. The paper applies the maximum likelihood method to estimate PFP and presents instructions to generate CTs by means of the bar method. The Monte Carlo method is used to carry out computer simulations.
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