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Master
unige:33672 
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Robust Estimation for Bivariate Distribution |
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| 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 distribution — Copula — Robust estimation — Indirect Inference — Income distribution | |
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| Citation (ISO format) | ORSO, Samuel. Robust Estimation for Bivariate Distribution. Université de Genève. Master, 2013. https://archive-ouverte.unige.ch/unige:33672 |
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