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PROBABILISTIC APPROACH TO RISKS ASSOCIATED WITH TRUNCATED DATA
Keywords:
probabilistic modeling, truncated data, random sampleDOI:
https://doi.org/10.17654/0972086326002Abstract
This article presents a contribution to probabilistic modeling risks linked to truncated data. We first model that the sample density of the last random sample is given by the truncation of the distribution function. Then we show that our estimator is unbiased, and also the inverse of the variance measures whatever the sample size, the precision of the estimator and if the distribution function is log-concave, then the precision is shown to be much lower than the value to be estimated.
Received: August 20, 2025
Revised: October 15, 2025
Accepted: October 30, 2025
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