  An Archimedean copula is characterised by its generator. This is a real
function whose inverse behaves as a survival function. We propose a
semiparametric generator based on a quadratic spline. This is achieved by
modelling the first derivative of a hazard rate function, in a survival
analysis context, as a piecewise constant function. Convexity of our
semiparametric generator is obtained by imposing some simple constraints. The
induced semiparametric Archimedean copula produces Kendall's tau association
measure that covers the whole range $(-1,1)$. Inference on the model is done
under a Bayesian approach and for some prior specifications we are able to
perform an independence test. Properties of the model are illustrated with a
simulation study as well as with a real dataset.
