= Time-rescaled spike-train diagnostics
{title2=$z_i=\int_{t_i}^{t_{i+1}}\lambda(t\mid\mathcal H_t)\,dt$}
For a correctly specified conditional rate, transformed interspike intervals have independent unit-exponential distributions, apart from observation-boundary censoring. Their transforms $1-e^{-z_i}$ should be uniform. Distributional checks and serial-correlation checks assess a fitted spike model on held-out data. A history-dependent model must include past spikes in its conditional rate; stimulus-only <Poisson spike-train likelihood fitting> cannot automatically capture refractoriness.
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