In this work, the postmortem interval is estimated by means of Bayesian inference using rectal temperature data from a published database. First, a systematic analysis of the uncertainties in each of the model parameters is carried out in order to assess their relative influences on the postmortem interval uncertainty. Then, the method is applied to the whole database and proves to be more reliable than the well-established nomogram method. Moreover, the result of the Bayesian inference process is the full posterior probability distribution of the postmortem interval, which provides more information than a simple point estimate or a time interval. This distribution can be used to assign probabilities to specific time intervals that may arise in a criminal investigation. The application of this statistical analysis can be extended to any method of estimating the postmortem interval.
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