Bayesian inference from measurement information

被引：15

作者：

Lira, I

Kyriazis, G

机构：

[1] Pontificia Univ Catolica Chile, Escuela Ingn, Santiago 22, Chile

[2] Natl Metrol Inst Brazil, INMETRO, BR-25250020 Rio De Janeiro, Brazil

来源：

METROLOGIA | 1999年 / 36卷 / 03期

关键词：

D O I：

10.1088/0026-1394/36/3/1

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Bayesian inference about a quantity is made through the probability density function that describes the state of incomplete knowledge acquired from measurement. This approach can be applied advantageously to evaluate the data obtained from repeated measurements of a quantity, with or without added information on the variances or error bounds of the indicated values. Results are compared with those obtained using conventional statistical theory. It is concluded that Bayesian inference allows a flexible and natural characterization of the measurement uncertainty.

引用

页码：163 / 169

页数：7

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