  The inspection of residuals is a fundamental step to investigate the quality
of adjustment of a parametric model to data. For spatial point processes, the
concept of residuals has been recently proposed by Baddeley et al. (2005) as an
empirical counterpart of the {\it Campbell equilibrium} equation for marked
Gibbs point processes. The present paper focuses on stationary marked Gibbs
point processes and deals with asymptotic properties of residuals for such
processes. In particular, the consistency and the asymptotic normality are
obtained for a wide class of residuals including the classical ones (raw
residuals, inverse residuals, Pearson residuals). Based on these asymptotic
results, we define goodness-of-fit tests with Type-I error theoretically
controlled. One of these tests constitutes an extension of the quadrat counting
test widely used to test the null hypothesis of a homogeneous Poisson point
process.
