The empirical likelihood method is known to be a flexible and effective approach for testing hypotheses and constructing confidence regions in a nonparametric setting. This framework is adopted here for dealing with the outlier problem in time series where conventional distributional assumptions may be inappropriate in most cases. The procedure is illustrated by a simulation experiment.
Baragona, R., Cucina, D. (2014). Outliers in Time Series: an Empirical Likelihood Approach. In Proceedings of the 47th Scientific Meeting of the Italian Statistical Society (pp. 1-6). ITA : CUEC Cooperativa Universitaria Editrice Cagliaritana.
Outliers in Time Series: an Empirical Likelihood Approach
Cucina D.
2014-01-01
Abstract
The empirical likelihood method is known to be a flexible and effective approach for testing hypotheses and constructing confidence regions in a nonparametric setting. This framework is adopted here for dealing with the outlier problem in time series where conventional distributional assumptions may be inappropriate in most cases. The procedure is illustrated by a simulation experiment.File in questo prodotto:
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