= Exact tied-set conditional likelihood
{title2=$L_D=\displaystyle\frac{\prod_{i\in D}u_i}{\sum_{A\subseteq R,\,|A|=d}\prod_{i\in A}u_i}$}
In a discrete-time model with independent event indicators whose odds are $a u_i$, condition on exactly $d$ events in the <risk set> $R$. The common factor $a^d$ cancels and the conditional probability of the event set $D$ is the displayed ratio. The denominator is an <elementary symmetric polynomial> and can be evaluated by recursion rather than enumerating every subset. This conditional model is distinct from summing a continuous-time rank <likelihood> over all unobserved within-tie orders.
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