uppose that the functions
depend on vector of unknown parameters
.
Recall that all the processes are Gaussian. According to the previous section
if we have a list of observations
then we can form a likelihood
function
where the
is the density of the normal random
variable
With the likelihood function known we can take a classical position and
maximize it (
Maximal likelihood
) or
take a Bayesian position (
Bayesian
statistics
) and do MCMC.
