Best Probability Density Function for Random Sampled Data

被引:7
|
作者
Jacobs, Donald J. [1 ]
机构
[1] Univ N Carolina, Dept Phys & Opt Sci, Charlotte, NC 28223 USA
关键词
maximum entropy method; probability density function; Lagrange multipliers; level-function moments; least squares error; adaptive simulated annealing; smoothing noise; HAUSDORFF MOMENT PROBLEM; MAXIMUM-ENTROPY; INFORMATION-THEORY;
D O I
10.3390/e11041001
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The maximum entropy method is a theoretically sound approach to construct an analytical form for the probability density function (pdf) given a sample of random events. In practice, numerical methods employed to determine the appropriate Lagrange multipliers associated with a set of moments are generally unstable in the presence of noise due to limited sampling. A robust method is presented that always returns the best pdf, where tradeoff in smoothing a highly varying function due to noise can be controlled. An unconventional adaptive simulated annealing technique, called funnel diffusion, determines expansion coefficients for Chebyshev polynomials in the exponential function.
引用
收藏
页码:1001 / 1024
页数:24
相关论文
共 50 条
  • [1] PROBABILITY DENSITY-ESTIMATION FROM SAMPLED DATA
    MASRY, E
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 1983, 29 (05) : 696 - 709
  • [2] The probability density function to the random linear transport equation
    Santos, L. T.
    Dorini, F. A.
    Cunha, M. C. C.
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2010, 216 (05) : 1524 - 1530
  • [3] Approximating the Probability Density Function of a Transformation of Random Variables
    Denys Pommeret
    Laurence Reboul
    [J]. Methodology and Computing in Applied Probability, 2019, 21 : 633 - 645
  • [4] Approximating the Probability Density Function of a Transformation of Random Variables
    Pommeret, Denys
    Reboul, Laurence
    [J]. METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 2019, 21 (02) : 633 - 645
  • [5] The influence of the probability density function on spectral quality in nonuniformly sampled multidimensional NMR
    Zambrello, Matthew A.
    Craft, D. Levi
    Hoch, Jeffrey C.
    Rovnyak, David
    Schuyler, Adam D.
    [J]. JOURNAL OF MAGNETIC RESONANCE, 2020, 311
  • [6] Variations in steepness of the probability density function of beam random vibration
    Steinwolf, A
    Ferguson, NS
    White, RG
    [J]. EUROPEAN JOURNAL OF MECHANICS A-SOLIDS, 2000, 19 (02) : 319 - 341
  • [7] A Method of Generating Random Vectors with a Given Probability Density Function
    Darkhovsky, B. S.
    Popkov, Yu. S.
    Popkov, A. Yu.
    Aliev, A. S.
    [J]. AUTOMATION AND REMOTE CONTROL, 2018, 79 (09) : 1569 - 1581
  • [8] Estimation of the probability density function of random displacements from images
    Ahmadzadegan, Adib
    Ardekani, Arezoo M.
    Vlachos, Pavlos P.
    [J]. PHYSICAL REVIEW E, 2020, 102 (03)
  • [9] On the Probability Density Function of the Product of Rayleigh Distributed Random Variables
    Widanagamage, Anushka
    Jayalath, Dhammika
    [J]. 6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS'2012), 2012,
  • [10] Estimation of probability density function of a random variable for small samples
    Srinivasan, VS
    [J]. DEFENCE SCIENCE JOURNAL, 2004, 54 (01) : 17 - 19