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1996•Journal of the Royal Statistical Society Series B (Statistical Methodology)Requires access

Estimation for Censored Exponential Data When the Censoring Times are Subject to Error

Michael John Phillips, Trevor J. Sweeting

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Abstract

SUMMARY The problem of estimating the parameter of the negative exponential distribution with censored data may be complicated by a lack of complete knowledge of the censoring times. The effect of ignoring these errors in the censoring times rather than using a complete maximum likelihood estimation approach is investigated and it is shown that the loss in efficiency is generally small for the inverted gamma model considered in this paper. The theory is supplemented by some numerical results based on an example of failure data.

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SUMMARY The problem of estimating the parameter of the negative exponential distribution with censored data may be complicated by a lack of complete knowledge of the censoring times. The effect of ignoring these errors in the censoring times rather than using a complete maximum likelihood estimation approach is investigated and it is shown that the loss in efficiency is generally small for the inverted gamma model considered in this paper. The theory is supplemented by some numerical results based on an example of failure data.

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Available abstract

SUMMARY The problem of estimating the parameter of the negative exponential distribution with censored data may be complicated by a lack of complete knowledge of the censoring times. The effect of ignoring these errors in the censoring times rather than using a complete maximum likelihood estimation approach is investigated and it is shown that the loss in efficiency is generally small for the inverted gamma model considered in this paper. The theory is supplemented by some numerical results based on an example of failure data.

Key concepts: Censoring (clinical trials), Exponential distribution, Statistics, Maximum likelihood, Exponential function, Econometrics, Mathematics, Computer science

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