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Robust Estimation for Bivariate Distribution

Denomination Master of Science in Statistics
Defense Master : Univ. Genève, 2013
Abstract Copula functions are very convenient for modelling multivariate observations. Popular estimation methods are the two-stage MLE and an alternative semi-parametric with empirical cdf for the margins. Unfortunately, they are hastily biased whenever relatively small model deviations occur at the marginal (empirical or parametric) and/or copula levels. In this master thesis we propose three robust estimators that do not share this undesirable feature. The bounded-bias of robust estimators is corrected through indirect inference. By means of a simulation study we show that the robust estimators outperform the popular approaches.
Keywords Bivariate distributionCopulaRobust estimationIndirect InferenceIncome distribution
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ORSO, Samuel. Robust Estimation for Bivariate Distribution. Université de Genève. Master, 2013. https://archive-ouverte.unige.ch/unige:33672

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Deposited on : 2014-01-24

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