Projection pursuit regression

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In mathematics, the generalized polygamma function or balanced negapolygamma function is a function introduced by Olivier Espinosa Aldunate and Victor H. Moll.[1]

It generalizes the polygamma function to negative and fractional order, but remains equal to it for integer positive orders.

Definition

The generalized polygamma function is defined as follows:

ψ(z,q)=ζ(z+1,q)+(ψ(z)+γ)ζ(z+1,q)Γ(z)

or alternatively,

ψ(z,q)=eγzz(eγzζ(z+1,q)Γ(z)),

where ψ(z) is the Polygamma function and ζ(z,q), is the Hurwitz zeta function.

The function is balanced, in that it satisfies the conditions f(0)=f(1) and 01f(x)dx=0.

Relations

Several special functions can be expressed in terms of generalized polygamma function.

where Bn(q) are Bernoulli polynomials

where K(z) is K-function and A is the Glaisher constant.

Special values

The balanced polygamma function can be expressed in a closed form at certain points:

References