On fractal distribution function estimation and applications
Theoretical background for affine IFS
Theorem 3 (Forte and Vrscay, 1995)
Theorem 4 (Iacus and La Torre, 2001).
Theorem 5 (Iacus and La Torre, 2001)
Theorem 8 (Forte and Vrscay, 1998)
Theorem 9 (Collage Theorem for FT, (Forte and Vrscay, 1998))
4.1 Asymptotic results for the quantile-based IFS estimator
Theorem 12 (Gill and Levit, 1995)
4.2 Characteristic function and Fourier density estimation
Given a set of N maps and probabilities (w, p), satisfying the properties i)- v) along with Wi : [0, 1] →[Ci, D i) then the fixed points of M : M([0, 1]) → M([0, 1]) and Tp : F([0, 1]) → F([0, 1]), say ~µ and ~ F respectively, relate as follows
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Proof. From the contractivity of M and Tp, there exist
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and
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fixed points of M and Tp, respectively. Let
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the thesis consists of proving
So we have:

By the uniqueness of the fixed points, we get
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The previous theorem allows to reuse the results of Forte and Vrscay (1995) and in particular gives another way of finding the solution of ( P ) in terms of ( Q ) at least on the simplex ΠN by letting δi = 0 in CN. This is true in particular if we choose the maps as in TF . To be more explicit: from now on the functional Tp is intended to have fixed maps w and all δi = 0.
Stefano M. Iacus, Davide La Torre

In this paper we review some recent results concerning the approximations of distribution functions and measures on [0, 1] based on iterated function systems.
Stefano M. Iacus, Davide La Torre