Abstract
AbstractPoint maximum likelihood estimators for parameters, mean number of failures, and failure rate in a non–homogeneous Poisson process are derived, when only count data from k identical processes are available. Approximate confidence intervals based on the parametric bootstrap technique are considered. The performances of both the point and interval estimation procedures are assessed via Monte Carlo simulation.
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