• DocumentCode
    829771
  • Title

    Deconvolving multivariate kernel density estimates from contaminated associated observations

  • Author

    Masry, Elias

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of California, La Jolla, CA, USA
  • Volume
    49
  • Issue
    11
  • fYear
    2003
  • Firstpage
    2941
  • Lastpage
    2952
  • Abstract
    We consider the estimation of the multivariate probability density function f(x1,...,xp) of X1,...,Xp of a stationary positively or negatively associated (PA or NA) random process {Xi}i=1∞ from noisy observations. Both ordinary smooth and super smooth noise are considered. Quadratic mean and asymptotic normality results are established.
  • Keywords
    convergence of numerical methods; deconvolution; noise; optimisation; probability; random processes; asymptotic normality; contaminated associated observations; deconvolution; multivariate kernel density estimates; multivariate probability density function; negatively associated random process; noisy observations; quadratic mean; smooth noise; stationary positively associated process; super smooth noise; Additive noise; Convergence; Data analysis; Deconvolution; Kernel; Multidimensional systems; Pattern recognition; Probability density function; Random processes; Random variables;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2003.818415
  • Filename
    1246016
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=829771