In this paper, we propose the copula-based maximum likelihood (ML) approach to estimate the multiple stochastic frontier (SF) models with correlated composite errors. The motivation behind the ...
This is a preview. Log in through your library . Abstract In a linear (or affine) functional model the principal parameter is a subspace (respectively an affine subspace) in a finite dimensional inner ...
Figure 1: Likelihood-based methods are less accurate than maximum parsimony (MP) under heterogeneous conditions. Figure 2: Parsimony outperforms likelihood over a wide range of heterotachous ...
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