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- W2085201310 abstract "Empirical likelihood for general estimating equations is a method for testing hypothesis or constructing confidence regions on parameters of interest. If the number of parameters of interest is smaller than that of estimating equations, a profile empirical likelihood has to be employed. In case of dependent data, a profile blockwise empirical likelihood method can be used. However, if too many nuisance parameters are involved, a computational difficulty in optimizing the profile empirical likelihood arises. Recently, Li et al. (2011) [9] proposed a jackknife empirical likelihood method to reduce the computation in the profile empirical likelihood methods for independent data. In this paper, we propose a jackknife–blockwise empirical likelihood method to overcome the computational burden in the profile blockwise empirical likelihood method for weakly dependent data." @default.
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- W2085201310 date "2012-02-01" @default.
- W2085201310 modified "2023-10-18" @default.
- W2085201310 title "Jackknife–blockwise empirical likelihood methods under dependence" @default.
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- W2085201310 doi "https://doi.org/10.1016/j.jmva.2011.06.009" @default.
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