A chi-square goodness-of-fit test for non-identically distributed random variables: with application to empirical Bayes

PDF Version Also Available for Download.

Description

When using parametric empirical Bayes estimation methods for estimating the binomial or Poisson parameter, the validity of the assumed beta or gamma conjugate prior distribution is an important diagnostic consideration. Chi-square goodness-of-fit tests of the beta or gamma prior hypothesis are developed for use when the binomial sample sizes or Poisson exposure times vary. Nine examples illustrate the application of the methods, using real data from such diverse applications as the loss of feedwater flow rates in nuclear power plants, the probability of failure to run on demand and the failure rates of the high pressure coolant injection systems at ... continued below

Physical Description

50 p.

Creation Information

Conover, W.J.; Cox, D.D. & Martz, H.F. December 1, 1997.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

Who

People and organizations associated with either the creation of this report or its content.

Authors

  • Conover, W.J. Texas Tech Univ., Lubbock, TX (United States)
  • Cox, D.D. Rice Univ., Houston, TX (United States)
  • Martz, H.F. Los Alamos National Lab., NM (United States)

Sponsor

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this report. Follow the links below to find similar items on the Digital Library.

Description

When using parametric empirical Bayes estimation methods for estimating the binomial or Poisson parameter, the validity of the assumed beta or gamma conjugate prior distribution is an important diagnostic consideration. Chi-square goodness-of-fit tests of the beta or gamma prior hypothesis are developed for use when the binomial sample sizes or Poisson exposure times vary. Nine examples illustrate the application of the methods, using real data from such diverse applications as the loss of feedwater flow rates in nuclear power plants, the probability of failure to run on demand and the failure rates of the high pressure coolant injection systems at US commercial boiling water reactors, the probability of failure to run on demand of emergency diesel generators in US commercial nuclear power plants, the rate of failure of aircraft air conditioners, baseball batting averages, the probability of testing positive for toxoplasmosis, and the probability of tumors in rats. The tests are easily applied in practice by means of corresponding Mathematica{reg_sign} computer programs which are provided.

Physical Description

50 p.

Notes

INIS; OSTI as DE98004319

Source

  • Other Information: PBD: Dec 1997

Language

Item Type

Identifier

Unique identifying numbers for this report in the Digital Library or other systems.

  • Other: DE98004319
  • Report No.: LA-UR--97-4825
  • Grant Number: W-7405-ENG-36
  • DOI: 10.2172/645488 | External Link
  • Office of Scientific & Technical Information Report Number: 645488
  • Archival Resource Key: ark:/67531/metadc694130

Collections

This report is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

What responsibilities do I have when using this report?

When

Dates and time periods associated with this report.

Creation Date

  • December 1, 1997

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

Description Last Updated

  • April 7, 2016, 7:38 p.m.

Usage Statistics

When was this report last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 3

Interact With This Report

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

Citations, Rights, Re-Use

Conover, W.J.; Cox, D.D. & Martz, H.F. A chi-square goodness-of-fit test for non-identically distributed random variables: with application to empirical Bayes, report, December 1, 1997; New Mexico. (digital.library.unt.edu/ark:/67531/metadc694130/: accessed August 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.