Random Field Models for Fitness Landscapes
Peter F. Stadler and Robert Happel
In many cases fitness landscapes are obtained as particular instances of
random fields by assigning a large number of random parameters. Models
of this type are often characterized reasonably well by their covariance
matrices. We characterize isotropic random fields on finite graphs in
terms of their Fourier series expansions and investigate the relation
between the covariance matrix of the random field model and the correlation
structure of the individual landscapes constructed from this random field.
Our formalism suggests to approximate landscape with known autocorrelation
function by a random field model that has the same correlation structure.
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