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
Under conditions i) to v):
1. Tp is an operator from
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to itself.
2. Suppose that wi(x) = x, P i = p, and δi ≥ −p, then
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3.
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then Tp is a contraction on
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with contractivity
constant c.
4. Let
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such that TpF1 = F1 and Tp* F2 = F2. Then

where c is the contractivity constant of Tp. The theorem above assures the IFS nature of the operator Tp that can be denoted, as in the previous section, as a N-maps IFS(w, p) with obvious notation. The goal is again the solution of the inverse problem in terms of p. Consider the following convex set:

then we have the following results:
... in Theorem 5
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