Locally Most Powerful Rank Tests for Multiple-Censored Data

K. G. Mehrotra, R. A. Johnson, G. K. Bhattacharyya

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


A locally most powerful rank test is derived for multiple censored data in the context of a two-sample problem where the alternatives involve a single parameter. With independent random samples X1,‥, Xm and Y1,‥, Yn, from F and G respectively, let the combined samnle order statistics be denoted by W1, ‥, WN where N = m+n. We present results for the triple censoring scheme where two blocks of order statistics, Wk1 to Wk2 and Wk3 to Wk4 are observed in addition to recording the number of X’s and Y's among the censored values. These extend the derivation of optimal rank tests for single censored data to the multiple censored situation.

Original languageEnglish (US)
Pages (from-to)459-469
Number of pages11
JournalCommunications in Statistics - Theory and Methods
Issue number5
StatePublished - Jan 1 1977


  • hazard rate
  • multiple censoring

ASJC Scopus subject areas

  • Statistics and Probability


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