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- """
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+ @doc raw """
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GibbsKernel(; lengthscale)
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- # Definition
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+ Gibbs Kernel with lengthscale function `lengthscale`.
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- The Gibbs kernel is non-stationary generalisation of the squared exponential
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+ The Gibbs kernel is a non-stationary generalisation of the squared exponential
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kernel. The lengthscale parameter ``l`` becomes a function of
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position ``l(x)``.
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- For a constant function``l(x) = c``, one recovers the standard squared exponential kernel
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- with lengthscale `c`.
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+ # Definition
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+ For inputs ``x, x'``, the Gibbs kernel with lengthscale function ``l(\c dot)``
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+ is defined as
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```math
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- k(x, y ; l) = \\ sqrt{ \\ left(\\ frac{2 l(x) l(y )}{l(x)^2 + l(y )^2} \\ right) }
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- \\ quad \\ rm{ exp} \\ left( - \\ frac{(x - y )^2}{l(x)^2 + l(y )^2} \\ right)
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+ k(x, x' ; l) = \s qrt{\ l eft(\f rac{2 l(x) l(x' )}{l(x)^2 + l(x' )^2}\ r ight)}
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+ \q uad \e xp{ \ l eft(- \ f rac{(x - x' )^2}{l(x)^2 + l(x' )^2}\ r ight)}.
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```
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+ For a constant function ``l \e quiv c``, one recovers the [`SqExponentialKernel`](@ref)
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+ with lengthscale `c`.
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+
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# References
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Mark N. Gibbs. "Bayesian Gaussian Processes for Regression and Classication." PhD thesis, 1997
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