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5 ta ish

Ish: Central limit theorem and the bootstrap for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" display="inline" overflow="scroll"><mml:mi>U</mml:mi></mml:math>-statistics of strongly mixing data

  1. Bootstrap for dependent Hilbert space-valued random variables with application to von Mises statistics

    Herold Dehling, Olimjon Sh. Sharipov, Martin Wendler

    MaqolaBayesian Methods and Mixture ModelsJournal of Multivariate Analysis20144 iqtibos
    ABI

  2. Bootstrap for the sample mean and for<i>U</i>-statistics of mixing and near-epoch dependent processes

    Olimjon Sh. Sharipov, Martin Wendler

    MaqolaFinancial Risk and Volatility ModelingJournal of nonparametric statistics20123 iqtibos
    ABI

  3. Bootstrap for the Sample Mean and for U-Statistics of Mixing and Near Epoch Dependent Processes

    Olimjon Sh. Sharipov, Martin Wendler

    PreprintFinancial Risk and Volatility ModelingarXiv (Cornell University)20090 iqtibos
    ABI

  4. Bootstrap for U-Statistics: A new approach

    Olimjon Sh. Sharipov, Johannes Tewes, Martin Wendler

    PreprintStatistical Methods and InferencearXiv (Cornell University)20150 iqtibos
    ABI

  5. Bootstrap for<i>U</i>-statistics: a new approach

    Sh. Olimjon Sharipov, Johannes Tewes, Martin Wendler

    MaqolaFinancial Risk and Volatility ModelingJournal of nonparametric statistics20160 iqtibos
    ABI