Analyzing survival data with highly negatively skewed distribution: The Gompertz-sinh family

Kahadawala Cooray, Malwane M.A. Ananda

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In this article, we explore a newtwo-parameter family of distribution, which is derived by suitably replacing the exponential term in the Gompertz distribution with a hyperbolic sine term. The resulting new family of distribution is referred to as the Gompertz-sinh distribution, and it possesses a thicker and longer lower tail than the Gompertz family, which is often used to model highly negatively skewed data. Moreover, we introduce a useful generalization of this model by adding a second shape parameter to accommodate a variety of density shapes as well as nondecreasing hazard shapes. The flexibility and better fitness of the new family, as well as its generalization, is demonstrated by providing well-known examples that involve complete, group, and censored data.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalJournal of Applied Statistics
Volume37
Issue number1
DOIs
StatePublished - Jan 2010

Keywords

  • Gompertz distribution
  • Goodness-of-fit
  • Maximum likelihood

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