Maximum entropy algorithm with inexact upper entropy bound based on Fup basis functions with compact support
2009 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 228, no 24, 9079-9091 p.Article in journal (Refereed) Published
The maximum entropy (MaxEnt) principle is a versatile tool for statistical inference of the probability density function (pdf) from its moments as a least-biased estimation among all other possible pdfs. It maximizes Shannon entropy, satisfying the moment constraints. Thus, the MaxEnt algorithm transforms the original constrained optimization problem to the unconstrained dual optimization problem using Lagrangian multipliers. The Classic Moment Problem (CMP) uses algebraic power moments, causing typical conventional numerical methods to fail for higher-order moments (m > 5-10) due to different sensitivities of Lagrangian multipliers and unbalanced nonlinearities. Classic MaxEnt algorithms overcome these difficulties by using orthogonal polynomials, which enable roughly the same sensitivity for all Lagrangian multipliers. In this paper, we employ an idea based on different principles, using Fup(n) basis functions with compact support, which can exactly describe algebraic polynomials, but only if the Fup order-n is greater than or equal to the polynomial's order. Our algorithm solves the CMP with respect to the moments of only low order Fup(2) basis functions, finding a Fup(2) optimal pdf with better balanced Lagrangian multipliers. The algorithm is numerically very efficient due to localized properties of Fup(2) basis functions implying a weaker dependence between Lagrangian multipliers and faster convergence. Only consequences are an iterative scheme of the algorithm where power moments are a sum of Fup(2) and residual moments and an inexact entropy upper bound. However, due to small residual moments, the algorithm converges very quickly as demonstrated on two continuous pdf examples - the beta distribution and a bi-modal pdf, and two discontinuous pdf examples - the step and double Dirac pdf. Finally, these pdf examples present that Fup MaxEnt algorithm yields smaller entropy value than classic MaxEnt algorithm, but differences are very small for all practical engineering purposes.
Place, publisher, year, edition, pages
2009. Vol. 228, no 24, 9079-9091 p.
Maximum entropy algorithm; Classic Moment Problem; Fup basis functions; Compact support
IdentifiersURN: urn:nbn:se:kth:diva-10653DOI: 10.1016/j.jcp.2009.09.011ISI: 000271790600008ScopusID: 2-s2.0-70350026655OAI: oai:DiVA.org:kth-10653DiVA: diva2:222647
Tidigare titel: Inexact Maximum Entropy algorithm based on Fup basis functions with compact support. QC 20100714. Updated from submitted to published 201203262009-06-092009-06-092012-03-26Bibliographically approved