This new book offers a thorough guide to the theory and methods of
progressive censoring for practitioners and professionals in
applied statistics, quality control, life testing and reliability
testing. In many industrial experiments involving lifetimes of
machines or units, experiments have to be terminated early due to a
variety of circumstances. Samples that arise from such experiments
are called censored samples, and a new, efficient alternative
method is referred to as "progressive censoring" (where the removal
of live units at time of failure is employed).
Progressive Censoring first introduces progressive sampling
foundations, then discusses various properties of progressive
samples. It also describes how to make exact or approximate
inferences for the different statistical models with samples based
on progressive censoring schemes. With many concrete examples, the
book points out the greater efficiency gained by using this scheme
instead of classical right-censoring methods.
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