ESTIMATION METHODS FOR THE MEAN OF THE EXPONENTIAL-DISTRIBUTION BASED ON GROUPED AND CENSORED-DATA

For grouped and censored data from an exponential distribution, the method of maximum likelihood (ML) does not in general yield a closed form estimate of the mean, and therefore, an iterative procedure must be used. This paper considers three approximate estimators of the mean: two approximate ML estimators and the mid-point estimator. Their performances are compared by Monte Carlo simulation to those of the ML estimator in terms of the mean square error and bias. The two approximate ML estimators are reasonable substitutes for the ML estimator unless the probability of censoring and the number of inspections are small. The effect of inspection schemes on the relative performances of the three approximate methods is investigated.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
1993-03
Language
ENG
Citation

IEEE TRANSACTIONS ON RELIABILITY, v.42, no.1, pp.87 - 96

ISSN
0018-9529
URI
http://hdl.handle.net/10203/65893
Appears in Collection
IE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
  • Hit : 168
  • Download : 0
  • Cited 0 times in thomson ci
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡClick to seewebofscience_button
⊙ Cited 16 items in WoSClick to see citing articles inrecords_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0