  A Bayesian approach is adopted to analyze the sequence of seismic events and
their magnitudes near Jo\~ao C\^amara which occurred mainly from 1983 to 1998
along the Samambaia fault. In this work, we choose a Bayesian model for the
process of occurrence times conditional on the observed magnitude values
following the same procedure suggested by Stavrakakis and Tselentis (1987). The
model parameters are determined on the basis of historical and physical
information. We generate posterior samples from the joint posterior
distribution of the model parameters by using a variant of the
Metropolis-Hastings algorithm. We use the results in a variety of ways,
including the construction of pointwise posterior confidence bands for the
conditional intensity of the point process as a function of time, as well as, a
posterior distribuition as a function of the mean of occurrence per unit time.
