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Approximation and invariance properties of one-dimensional probabilities

  • Author / Creator
    Xu,Chuang
  • Approximation of probability measures, quantization, Kantorovich metric, Levy metric, Kolmogorov metric, Benford's Law, slowly changing sequences, asymptotic distribution, invariance property.","This thesis is based on four papers. The first two papers fall into the field of approximation of one-dimensional probabilities, the third into uniform distribution theory, and the last paper relates to ergodic theory.

    The first paper (joint with Arno Berger), \hfill studies best finitely supported approximations\ \noindent of one-dimensional probability measures with respect to (w.r.t.) the $L^r$-Kantorovich (or transport) distance, where either the
    locations or the weights of the approximations' atoms are
    prescribed. Special attention is given to the case of
    best uniform approximations (i.e., all atoms having equal weight).

    In the second paper (joint with Arno Berger), for arbitrary one-dimensional Borel probability measures with compact
    support, characterizations are established of the best finitely
    supported approximations, relative to three familiar probability
    metrics (L\'{e}vy, Kantorovich, and Kolmogorov), given any number of
    atoms, and allowing for additional constraints regarding weights or
    positions of atoms. As an application, best (constrained or
    unconstrained) approximations are identified for Benford's Law
    (logarithmic distribution of significands).

    The third paper studies the distributional asymptotics of the slowly changing sequence of logarithms $(\log_bn)$ with integer base $b\ge2.$ An upper estimate $\lt(N^{-1}\lt(\log N\rt)^{1/2}\rt)$ is obtained for the rate of convergence w.r.t. the Kantorovich metric on the circle. Moreover, a sharp rate of convergence $\lt(N^{-1}\log N\rt)$ w.r.t. the Kantorovich and the discrepancy (or Kolmogorov) metrics on the real line is derived.

    The last paper proves a threshold result on the existence of a circularly invariant and uniform probability measure (CIUPM) for non-constant linear transformations on the real line, which shows that there is a constant $c$ depending only on the slope of the linear transformation such that there exists a CIUPM if and only if the diameter of the support is not smaller than $c$. Moreover, the CIUPM is unique up to translation when the diameter of the support is equal to $c.$

  • Subjects / Keywords
  • Graduation date
    Fall 2018
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R33R0Q903
  • License
    Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.