IDEAS home Printed from https://ideas.repec.org/p/cte/wsrepe/ws033107.html

A bayesian analysis of beta testing

Author

Listed:
  • Wiper, Michael Peter
  • Wilson, Simon P.

Abstract

In this article, we define a model for fault detection during the beta testing phase of a software design project. Given sampled data, we illustrate how to estimate the failure rate and the number of faults in the software using Bayesian statistical methods with various different prior distributions. Secondly, given a suitable cost function, we also show how to optimise the duration of a further test period for each one of the prior distribution structures considered.

Suggested Citation

  • Wiper, Michael Peter & Wilson, Simon P., 2003. "A bayesian analysis of beta testing," DES - Working Papers. Statistics and Econometrics. WS ws033107, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:ws033107
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/rest/api/core/bitstreams/300053ac-fda3-4b81-ab0f-d5446e50102c/content
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Guoxiong, 2012. "Bayesian estimation of exchange rate regime choice with spatial effect," Economics Letters, Elsevier, vol. 117(3), pages 604-607.
    2. Li, Yong & Yu, Jun, 2012. "Bayesian hypothesis testing in latent variable models," Journal of Econometrics, Elsevier, vol. 166(2), pages 237-246.
    3. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    4. Kakamu, Kazuhiko & Yunoue, Hideo & Kuramoto, Takashi, 2014. "Spatial patterns of flypaper effects for local expenditure by policy objective in Japan: A Bayesian approach," Economic Modelling, Elsevier, vol. 37(C), pages 500-506.
    5. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    6. Lee, Sik-Yum & Song, Xin-Yuan, 2008. "On Bayesian estimation and model comparison of an integrated structural equation model," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4814-4827, June.
    7. Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(4), pages 230-354, June.
    8. Nikolay Arefiev & Ramis Khabibullin, 2018. "Bayesian identification of structural vector autoregression models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 49, pages 115-142.
    9. Timothy Cogley & Argia M. Sbordone, 2006. "Trend inflation and inflation persistence in the New Keynesian Phillips curve," Staff Reports 270, Federal Reserve Bank of New York.
    10. Hedibert Freitas Lopes, 2014. "A Tutorial on the Computation of Bayes Factors," Business and Economics Working Papers 200, Unidade de Negocios e Economia, Insper.
    11. Yoosoon Chang & Fei Tan & Xin Wei, 2018. "State Space Models with Endogenous Regime Switching," CAEPR Working Papers 2018-012, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    12. Keisuke Kondo, 2022. "Spatial dependence in regional business cycles: evidence from Mexican states," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-46, December.
    13. Gary Bolton & Duncan Fong & Paul Mosquin, 2003. "Bayes Factors with an Application to Experimental Economics," Experimental Economics, Springer;Economic Science Association, vol. 6(3), pages 311-325, November.
    14. Chan Joshua & Doucet Arnaud & León-González Roberto & Strachan Rodney W., 2025. "Multivariate Stochastic Volatility with Co-Heteroscedasticity," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 29(3), pages 265-300.
    15. Jouchi Nakajima & Yasuhiro Omori, 2007. "Leverage, Heavy-Tails and Correlated Jumps in Stochastic Volatility Models (Revised in January 2008; Published in "Computational Statistics and Data Analysis", 53-6, 2335-2353. April 2009. )," CARF F-Series CARF-F-107, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    16. Mike K. P. So & C. Y. Choi, 2009. "A threshold factor multivariate stochastic volatility model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(8), pages 712-735.
    17. Warne, Anders & Droumaguet, Matthieu & Woźniak, Tomasz, 2015. "Granger causality and regime inference in Bayesian Markov-Switching VARs," Working Paper Series 1794, European Central Bank.
    18. Roberto León-González, 2019. "Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility," Econometric Reviews, Taylor & Francis Journals, vol. 38(8), pages 899-920, September.
    19. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    20. Lo, Ming Chien & Morley, James, 2015. "Bayesian analysis of nonlinear exchange rate dynamics and the purchasing power parity persistence puzzle," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 285-302.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cte:wsrepe:ws033107. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ana Poveda (email available below). General contact details of provider: http://portal.uc3m.es/portal/page/portal/dpto_estadistica .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.