Progressively Censored Bivariate Normal Samples

Summary In response‐time studies where exact measurements are available over only part of the range, progressively censored samples arise when at various stages of an experiment, some, though not all, of the unreacted sample specimens are eliminated from further observation. The sample specimens remaining after each stage of censoring are continued under observation until they respond or until a subsequent stage of censoring. In this paper, the maximum‐likelihood equations of the distribution parameters, from progressively censored bivariate normal samples, are derived. For a solution of these equations an iterative procedure, simple to operate, which is not so vulnerable to divergence is suggested, and its comparison with the standard Newton–Raphson method is made. The information matrix is given from which the asymptotic variances and covariances of the estimates of the parameters may be obtained.