Tomoyuki Nakagawa, Ryoma Namba, Kiyotaka Iki, S. Tomizawa
{"title":"方形列联表偏对称性测度的改进近似无偏估计","authors":"Tomoyuki Nakagawa, Ryoma Namba, Kiyotaka Iki, S. Tomizawa","doi":"10.55937/sut/1641859470","DOIUrl":null,"url":null,"abstract":". For square contingency tables, the measure to represent the degree of departure from the partial symmetry model was proposed. It is necessary to estimate the measure because it is constructed of unknown parameters. Al-though many studies consider using the plug-in estimator to estimate the measure, the bias of the plug-in estimator is large when the sample size is not so large. In this study, we consider to estimate the measure when the sample size is not so large. This paper presents the improved approximate unbiased estimators of the measure which are obtained using the second-order term in Taylor series expansion. Some simulation studies show the performances of proposed estimators for finite sample cases.","PeriodicalId":38708,"journal":{"name":"SUT Journal of Mathematics","volume":"320 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved approximate unbiased estimators of the measure of departure from partial symmetry for square contingency tables\",\"authors\":\"Tomoyuki Nakagawa, Ryoma Namba, Kiyotaka Iki, S. Tomizawa\",\"doi\":\"10.55937/sut/1641859470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". For square contingency tables, the measure to represent the degree of departure from the partial symmetry model was proposed. It is necessary to estimate the measure because it is constructed of unknown parameters. Al-though many studies consider using the plug-in estimator to estimate the measure, the bias of the plug-in estimator is large when the sample size is not so large. In this study, we consider to estimate the measure when the sample size is not so large. This paper presents the improved approximate unbiased estimators of the measure which are obtained using the second-order term in Taylor series expansion. Some simulation studies show the performances of proposed estimators for finite sample cases.\",\"PeriodicalId\":38708,\"journal\":{\"name\":\"SUT Journal of Mathematics\",\"volume\":\"320 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SUT Journal of Mathematics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.55937/sut/1641859470\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SUT Journal of Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55937/sut/1641859470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
Improved approximate unbiased estimators of the measure of departure from partial symmetry for square contingency tables
. For square contingency tables, the measure to represent the degree of departure from the partial symmetry model was proposed. It is necessary to estimate the measure because it is constructed of unknown parameters. Al-though many studies consider using the plug-in estimator to estimate the measure, the bias of the plug-in estimator is large when the sample size is not so large. In this study, we consider to estimate the measure when the sample size is not so large. This paper presents the improved approximate unbiased estimators of the measure which are obtained using the second-order term in Taylor series expansion. Some simulation studies show the performances of proposed estimators for finite sample cases.