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Law of large numbers for discretely observed random functions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10365484" target="_blank" >RIV/00216208:11320/17:10365484 - isvavai.cz</a>

  • Result on the web

    <a href="http://www.sciencedirect.com/science/article/pii/S1226319217300261" target="_blank" >http://www.sciencedirect.com/science/article/pii/S1226319217300261</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.jkss.2017.04.002" target="_blank" >10.1016/j.jkss.2017.04.002</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Law of large numbers for discretely observed random functions

  • Original language description

    A strong law of large numbers for continuous random functions, and associated tensor product surfaces is established in the setup of discretely observed functional data. The result is shown in the framework of uniform convergence of functions, and stated without imposing any distributional assumptions. It is demonstrated that, under mild conditions, laws of large numbers for continuously observed functional data imply the corresponding laws under the discrete observational design of functions. Applications to the problem of estimation of expectation functions and covariance surfaces for discretely observed functional data are discussed.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2017

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of the Korean Statistical Society

  • ISSN

    1226-3192

  • e-ISSN

  • Volume of the periodical

    2017

  • Issue of the periodical within the volume

    46 (4)

  • Country of publishing house

    KR - KOREA, REPUBLIC OF

  • Number of pages

    11

  • Pages from-to

    562-572

  • UT code for WoS article

    000416613100006

  • EID of the result in the Scopus database

    2-s2.0-85018408842