In this paper we deal with the identification of an autoregressive model for
an observed time series, and the detection of a unit root in its
characteristic polynomial. This is a big issue concerned with distinguishing
stationary time series from time series for which differencing is required to
induce stationarity. We consider a Bayesian approach, and particular attention
is devoted to the problem of the sensitivity of the standard Bayesian analysis
with respect to the choice of the prior distribution for the autoregressive coefficients
