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7 та иш

Иш: Association of Random Variables, with Applications

  1. Central limit theorem and invariance principle for associated random fields

    Abdurakhman Mukhamedov

    МақолаProbability and Risk ModelsAIP conference proceedings20211 иқтибос
    ABI

  2. Comparison Results for GARCH Processes

    Fabio Bellini, Franco Pellerey, Carlo Sgarra +1

    ПрепринтFinancial Risk and Volatility ModelingJournal of Applied Probability20120 иқтибос
    ABI

  3. Uniform convergence of an estimator of empirical survival function and nuclear estimates of density from stationary sequences of strongly linearly positive quadrant dependent random variables

    Abdurakhman Muhamedov

    МақолаProbability and Risk ModelsAIP conference proceedings20230 иқтибос
    ABI

  4. Asymptotical properties of the estimator of two-dimensional distributions from stationary sequences of positively quadrant dependent random variables

    Abdurakhman Muhamedov

    МақолаProbability and Risk ModelsAIP conference proceedings20230 иқтибос
    ABI

  5. Strong consistency of density function estimates from stationary sequences of linearly positive quadrant dependent random variables

    Abdurahman Muhamedov

    МақолаProbability and Risk ModelsAIP conference proceedings20230 иқтибос
    ABI

  6. Convergence test statistic of kernel estimators of a density function from stationary sequence of strongly linearly positive quadrant dependent random variables

    Abdurakhman Muhamedov

    МақолаProbability and Risk ModelsAIP conference proceedings20240 иқтибос
    ABI

  7. Moment Inequality, Central Limit Theorem, and the Invariance Principle for Linearly Positive Quadrant Dependent Random Fields

    Abdurakhman Mukhamedov

    МақолаProbability and Risk ModelsUkrainian Mathematical Journal20250 иқтибос
    ABI