教師資料查詢 | 類別: 期刊論文 | 教師: 陳主智 CHEN CHU-CHIH (瀏覽個人網頁)

標題:Bayesian nonparametrics for compliance to exposure standards
學年82
學期1
出版(發表)日期1993/12/01
作品名稱Bayesian nonparametrics for compliance to exposure standards
作品名稱(其他語言)
著者Symons, Michael J.; 陳主智; Chen, Chu-chih; Flynn, Michael R.
單位淡江大學數學學系
出版者American Statistical Association
著錄名稱、卷期、頁數Journal of the American Statistical Association 88(424), pp.1237-1241
摘要A Bayesian nonparametric view of compliance to occupational standards is achieved through predictive distributions. The common assumption of lognormality of environmental exposures is relaxed while recognizing the practicality of a finite number of possible samples. These probability of compliance calculations are conditional on observing some of the samples. Familiar binomial and normal modes are identified with the classical perspective as limits of Bayesian nonparametric and parametric strategies, when the number of observed samples increases. In this situation, extensive previous sample data provide a correspondence between the classical and Bayesian approaches, rather than little or no previous information. Using an example, alternative procedures are illustrated and compared. Currently used methodology can be anti-conservative for protecting employees.
關鍵字Nuisance parameters;Predictive distributions
語言英文(美國)
ISSN0162-1459
期刊性質國外
收錄於
產學合作
通訊作者
審稿制度
國別美國
公開徵稿
出版型式,紙本
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