Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models

NeurIPS 2010 Felipe GerhardWulfram Gerstner

Generalized Linear Models (GLMs) are an increasingly popular framework for modeling neural spike trains. They have been linked to the theory of stochastic point processes and researchers have used this relation to assess goodness-of-fit using methods from point-process theory, e.g. the time-rescaling theorem... (read more)

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