A Bayesian approach to the analysis of industrial experiments: An illustration with binomial count data

Quality Engineering

Volumn 20, Issue 3, 2008, Pages 269-280

  Weaver, Brian P ^a   Hamada, Michael S ^b  

^a Department of Statistics Center for Statistics and Applications in Forensic Evidence Iowa State University 2438 Osborn Dr Ames   (United States)

^b LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

Bayesian 2 goodness of fit test; Bayesian information criterion; Contour plot; Experimental factor; Factorial design; Logistic regression; Markov chain Monte Carlo; Optimal factor level; Prediction; Response surface

Indexed keywords

CURVE FITTING; EXPERIMENTS; FOOD PROCESSING; MATERIALS HANDLING; MODAL ANALYSIS; REGRESSION ANALYSIS; STATISTICAL METHODS;

BAYESIAN APPROACHES; BAYESIAN METHODS; GOODNESS OF FIT (GOF); INTEGRATED FRAMEWORKS; LOGISTIC REGRESSION (LR) MODEL; MODEL SELECTIONS; RESPONSE SURFACE ESTIMATION; STATISTICAL PROBLEMS;

BAYESIAN NETWORKS;

EID: 47049091930     PISSN: 08982112     EISSN: 15324222     Source Type: Journal    
DOI: 10.1080/08982110701810451     Document Type: Article

References (11)

1. Casella, G. and Berger, R. L. (2002) Statistical Inference, Duxbury Press, North Scituate, MA
2. Casella, G. and George, E. I. (1992) Explaining the Gibbs sampler. The American Statistician, 46:3, pp. 167-174.
3. Chib, S. and Greenberg, E. (1995) Understanding the Metropolis-Hastings algorithm. The American Statistician, 49:4, pp. 327-335.
4. Chipman, H. and Hamada, M. (1996) Bayesian analysis of ordered categorical data from industrial experiments. Technometrics, 38, pp. 1-10.
5. Cox, D. R. and Snell, E. J. (1996) Analysis of Binary Data, Chapman and Hall, London
6. Hamada, M. and Wu, C. F. J. (1995) Analysis of censored data from fractionated experiments: A Bayesian approach. Journal of the American Statistical Association, 90, pp. 467-477.
7. Hosmer, D. A. and Lemeshow, S. (2000) Applied Logistic Regression, John Wiley & Sons, New York
8. 2 test for goodness-of-fit. Annals of Statistics, 32:6, pp. 2361-2384.
9. (2004) R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna
10. Spiegelhalter, D., Thomas, A., Best, N. and Lunn, D. (2007) WinBUGS Version 1.4.2 User Manual
11. Wu, C. F. J. and Hamada, M. (2000) Experiments: Planning, Analysis and Parameter Design Optimization, John Wiley & Sons, New York