Bayes Reliability Measures of Lognormal and Inverse Gaussian Distributions under ML-II e-contaminated Class of Prior Distributions

Authors

  • Pankaj Sinha University of Delhi, Delhi
  • J. Prabha University of Delhi, Delhi

DOI:

https://doi.org/10.14429/dsj.60.486

Keywords:

Bayes reliability, lognormal distribution, inverse Gaussian distribution, Bayesian methodology

Abstract

ML-II e-contaminated class of priors are employed to study the sensitivity of Bayes reliability measures for a lognormal (LN) distribution and inverse Gaussian (IG) distribution to mis-specification in the prior is employed. The numerical illustrations suggest that reliability measures of both the distributions are not sensitive to moderate amount of mis-specification in prior distributions belonging to the class of ML-II e-contaminated.

Defence Science Journal, 2010, 60(4), pp.442-450, DOI:http://dx.doi.org/10.14429/dsj.60.486

Author Biographies

Pankaj Sinha, University of Delhi, Delhi

Received his PhD in Bayesian Econometrics from University of Delhi. Presently he is an Assoc Prof at Faculty of Management Studies, University of Delhi.

J. Prabha, University of Delhi, Delhi

Obtained her MPhil in Statistics from University of Delhi. Presently she is pursuing PhD in Statistics on empirical Bayes approach to modelling financial volatility, asset pricing and portfolio selection from University of Delhi.

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Published

2010-07-09

How to Cite

Sinha, P., & Prabha, J. (2010). Bayes Reliability Measures of Lognormal and Inverse Gaussian Distributions under ML-II e-contaminated Class of Prior Distributions. Defence Science Journal, 60(4), 442–450. https://doi.org/10.14429/dsj.60.486

Issue

Vol. 60 No. 4: Machine Learning and Pattern Recognition

Section

Research Papers

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