Go to Header Go to Main Navigation Go to Content Go to Footer
  • Ohjeet
  • Kirjaudu sisään (ulkop. käyttäjät)
  • Kirjaudu sisään (JY-tunnus)
  • Saavutettavuus
  • English (GB)
Converis - etusivu
    Asiasanaluettelo > Monte Carlo -menetelmät
    • Etusivu
    • Asiantuntijat
    • Organisaatiot
    • Hankkeet
    • Julkaisut
    • Tutkimusaineistot
    • Tieteenalat
    • YSO-asiasanat

    Monte Carlo -menetelmät


    http://www.yso.fi/onto/yso/p6361


    Liittyvät julkaisut

    Go to first page
    Go to previous page
    1/2
    Go to next page
    Go to last page
    • An Updated Guideline for Assessing Discriminant Validity (2020) Rönkkö, Mikko; et al.; A1; OA
    • Coupled conditional backward sampling particle filter (2020) Lee, Anthony; et al.; A1; OA
    • Ergonomic and Reliable Bayesian Inference with Adaptive Markov Chain Monte Carlo (2020) Vihola, Matti; A3; 978-1-118-44511-2
    • Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance (2020) Franks, Jordan; et al.; A1; OA
    • Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo (2020) Vihola, Matti; et al.; A1; OA
    • Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods (2020) Pihlajamäki, Antti; et al.; A1; OA
    • On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction (2020) Vihola, Matti; et al.; A1; OA
    • CLEASE : A versatile and user-friendly implementation of Cluster Expansion method (2019) Chang, Jin Hyun; et al.; A1; OA
    • Data augmentation under Rician noise model in diffusion MRI with applications to human brain studies (2019) Liu, Jia; G5; OA
    • Markov Chain Monte Carlo Importance Samplers for Bayesian Models with Intractable Likelihoods (2019) Franks, Jordan; G5; OA

    Viimeisin päivitys 2019-09-04 klo 12:29

       
     


    Tutkimustietojärjestelmän käyttöönottoprojekti

    converis-support@jyu.fi

    Palveluita tutkijalle (HelpJYU)

    Tietosuojaseloste