Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The bootstrap can be validated by considering the sequence of P values obtained by bootstrap iteration, rather than asymptotically. If this sequence converges to a random variable with the uniform U(0,1) distribution, the bootstrap is valid. Here, the model is made discrete and finite, characterised by a three-dimensional array of probabilities. This renders bootstrap iteration to any desired order feasible. A unit-root test for a process driven by a stationary MA(1) process is known to be unreliable when the MA(1) parameter is near −1. Iteration of the bootstrap P value to convergence achieves reliable inference unless the parameter value is very close to −1.