  To estimate cosmological parameters from a given dataset, we need to
construct a likelihood function, which sometimes has a complicated functional
form. We introduce the copula, a mathematical tool to construct an arbitrary
multivariate distribution function from one-dimensional marginal distribution
functions with any given dependence structure. It is shown that a likelihood
function constructed by the so-called Gaussian copula can reproduce very well
the n-dimensional probability distribution of the cosmic shear power spectrum
obtained from a large number of ray-tracing simulations. This suggests that the
Copula likelihood will be a powerful tool for future weak lensing analyses,
instead of the conventional multivariate Gaussian likelihood.
