Confidence Interval Estimation in the Class of Modified Power Series Distributions

F. F. Famoye, P. C. Consul

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


The problem of interval estimation for the class of modified power series distribution (MPSD) is considered in this paper. Both the cases of small and large samples are investigated in setting 100 (1 - a) % confidence bounds for the parameter. By using the critical region for the uniformly most powerful test, we obtain a uniformly most accurate one-sided confidence bound. The general results are then applied to the generalized POISSON, generalized negative binomial and generalized logarithmic series distributions and particular results are derived for them.

Original languageEnglish
Pages (from-to)141-143
Number of pages3
Issue number1
StatePublished - Jan 1 1989


  • Modified power series distribution
  • confidence intervals
  • generalized POISSON distribution
  • generalized logarithmic series distribution
  • generalized negative binomial distribution
  • uniformly most accurate confidence bound
  • uniformly most powerful test


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