A General and Operational Representation of Generalised Extreme Value Models

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Choice Probability Generating Functions (2012, background): “Papers that deal with choice-probability generating functions for nested logit and what econometricians term generalized extreme value models are McFadden (1978), Daly and Bierlaire (2006) and Bierlaire et al. (2008).”
Accommodating Spatial Correlation Across Choice Alternatives in Discrete Choice Models: Application to Modeling Residential Location Choice Behavior (2011, methodology): “Several models have been developed within the GEV class, as recently discussed by Daly and Bierlaire (2006), Koppelman and Sethi (2008), and Bekhor and Prashker (2008).”
The estimation of generalized extreme value models from choice-based samples (2008, methodology): “This can be viewed as a Network GEV model (see Daly and Bierlaire, 2006) where the nodes just below the root share the same homogeneity parameter.”
A method of integrating correlation structures for a generalized recursive route choice model (2016, methodology): “In this section, we generalize the RL and NRL models by assuming the choice at each stage to be a network MEV model ( Daly and Bierlaire, 2006 ).”
The logsum as an evaluation measure - review of the literature and new results (2007, methodology): “The most general model of this type is the Network or Recursive Nested Extreme Value model, described by Daly and Bierlaire (2006), who give a recursive generalisation of the logsum formula as Corollary 8 of their main result.”