Moment-type estimation for Type-I censored samples.

The article concerns the problem of parameter estimation for Type-I censored data using general estimating equations. It proposes a new class of estimators that are analogs to the estimators obtained by the method of moments for complete samples. It is proved that the proposed estimators are exactly the maximum likelihood estimators in the class of distributions from the exponential family. The asymptotic properties of the presented estimators are compared to the maximum likelihood ones. The obtained results are presented jointly with a simulation study and computational examples. [ABSTRACT FROM AUTHOR]