Genome-wide analysis of macrosatellite repeat copy number variation in worldwide populations: evidence for differences and commonalities in size distributions and size restrictions von Schaap, Mireille, Lemmers, Richard J L F, Maassen, Roel, van der Vliet, Patrick J, Hoogerheide, Lennart F, van Dijk, Herman K, Baştürk, Nalan, de Knijff, Peter, van der Maarel, Silvère M

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GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts von Ardia, David, Hoogerheide, Lennart F.

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Methods for Computing Numerical Standard Errors: Review and Application to Value-at-Risk Estimation von Ardia, David, Bluteau, Keven, Hoogerheide, Lennart F.

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Worldwide equity risk prediction von Ardia, David, Hoogerheide, Lennart F.

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Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations von Ardia, David, Hoogerheide, Lennart,F.

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A Note on Jointly Backtesting Models for Multiple Assets and Horizons von Ardia, David, Guerrouaz, Anas, Hoogerheide, Lennart F.

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Density prediction of stock index returns using GARCH models: Frequentist or Bayesian estimation? von Hoogerheide, Lennart F., Ardia, David, Corré, Nienke

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On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural network... von Hoogerheide, Lennart F., Kaashoek, Johan F., van Dijk, Herman K.

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Cross-Sectional Distribution of GARCH Coefficients Across S&P 500 Constituents: Time-Variation Over the Period 2000-2012 von Ardia, David, Hoogerheide, Lennart F.

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Adaptive Mixture of Student- t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit von Ardia, David, Hoogerheide, Lennart F., Dijk, Herman K. van

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Adaptive Mixture of Student-t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit von David Ardia, Lennart F. Hoogerheide, Herman K. van Dijk

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AdMit von Ardia, David, Hoogerheide, Lennart,F., Dijk, Herman,K.,van

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Simulation‐Based Bayesian Econometric Inference: Principles and Some Recent Computational Advances von Hoogerheide, Lennart F, van Dijk, Herman K, van Oest, Rutger D

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