Draws the outcome indicator \(J \sim \mathrm{Bernoulli}(q)\) and the
terminal log-odds from the exact transition law
\(L_T = L + (1\{J=1\} - 1/2)A + \sqrt{A}\,\zeta\). The martingale
property \(E[q_T] = q\) holds by construction (Bayes consistency of
the \(\pm A/2\) drift).
Arguments
- n
Integer, number of draws.
- q
Numeric vector of current event probabilities in \((0,1)\).
- A
Numeric vector of event-clock time (non-negative).
Value
A tibble with columns J (0/1 outcome), zeta, L_T, and
q_T.
Examples
set.seed(1)
sim <- ec_simulate(1e4, q = 0.195, A = 0.166)
mean(sim$q_T) # close to 0.195
#> [1] 0.1940241
mean(sim$J) # close to 0.195
#> [1] 0.2024
