Compound gamma, beta and F distributions

@article{Dubey1970CompoundGB,
  title={Compound gamma, beta and F distributions},
  author={S D Dubey},
  journal={Metrika},
  year={1970},
  volume={16},
  pages={27-31}
}
SummaryIn this paper a compound gamma distribution has been derived by compounding a gamma distribution with another gamma distribution. The resulting compound gamma distribution has been reduced to the Beta distributions of the first kind and the second kind and to theF distribution by suitable transformations. This includes theLomax distribution as a special case which enjoys a useful property. Moment estimators for two of its parameters are explicitly obtained, which tend to a bivariate… Expand
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References

Business Failures: Another Example of the Analysis of Failure Data
TLDR
An analysis of data on failures of four types of business in Poughkeepsie, New York, from 1844 to 1926 confirms that the conditional probabilities of failure for these four series are well described by both exponential and hyperbolic functions. Expand