Maximum likelihood estimation for a bivariate Gaussian process under   fixed domain asymptotics
  We consider maximum likelihood estimation with data from a bivariate Gaussian process with a separable exponential covariance model under fixed domain asymptotic. We first characterize the equivalence of Gaussian measures under this model. Then consistency and asymptotic distribution for the microergodic parameters are established. A simulation study is presented in order to compare the finite sample behavior of the maximum likelihood estimator with the given asymptotic distribution. 
Daira Velandia, Fran\c{c}ois Bachoc (IMT, GdR MASCOT-NUM), Moreno   Bevilacqua, Xavier Gendre (IMT), Jean-Michel Loubes (IMT)
math.ST stat.TH