  Probability models are proposed for passage time data collected in
experiments with a device designed to measure particle flow during aerial
application of fertilizer. Maximum likelihood estimation of flow intensity is
reviewed for the simple linear Boolean model, which arises with the assumption
that each particle requires the same known passage time. M-estimation is
developed for a generalization of the model in which passage times behave as a
random sample from a distribution with a known mean. The generalized model
improves fit in these experiments. An estimator of total particle flow is
constructed by conditioning on lengths of multi-particle clumps.
