Dear all, it's known how to derive the covariance values cov(h) of a lognormal process Z(s) from those of its corresponding gaussian process Y(s). Is it possible to derive the covariance function (i.e. form and parameters) of Z(s) from the one of Y(s)?
If I calculate covariance values for many distances from a given covariance function and transform these values to lognormal ones, I don't even seem to be able to find a covariance function which goes right through all of them... [I'm completely lost here.] Thanks and regards, Dominik
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