Campus Units

Industrial and Manufacturing Systems Engineering, Mechanical Engineering, Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2006

Journal or Book Title

IEEE Transactions on Instrumentation and Measurement

Volume

55

Issue

6

First Page

2165

Last Page

2171

DOI

10.1109/TIM.2006.884128

Abstract

n this paper, hierarchical Bayes analyses of an experiment conducted to enable calibration of a set of mass-produced resistance temperature devices (RTDs) are considered. These were placed in batches into a liquid bath with a precise National Institute of Standards and Technology (NIST)-approved thermometer, and resistances and temperatures were recorded approximately every 30 s. Under the assumptions that the thermometer is accurate and each RTD responds linearly to temperature change, hierarchical Bayes methods to estimate the parameters of the linear calibration equations are used. Predictions of the parameters for an untested RTD of the same type and interval estimates of temperature based on a realized resistance reading are also available for both the tested RTDs and an untested one.

Comments

This is a manuscript of an article published as "Hierarchical Bayes statistical analyses for a calibration experiment." IEEE Transactions on Instrumentation and Measurement, 2006, Vol. 55, No. 6, pp. 2165-2171. With Reid Landes and Peter Loutzenhiser. Posted with permission.

Rights

© 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright Owner

IEEE

Language

en

File Format

application/pdf

Published Version

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