Risk-efficient estimation of the mean exponential survival time under random censoring

The paper proposes a sequential estimator theta of the parameter theta of an exponential distribution when the data are censored. It is shown that theta is asymptotically risk efficient when the loss is measured by the squared error of estimation of theta plus a linear function of the number of observations and that theta is asymptotically normal as the cost per observation goes to zero.