Table 2.

Iterative simulation fitting

Sequence	Iterations	Trials	p(K–S)A	p(K–S)B	μstop
1	16	4800	0.71	0.96	15.88
2	17	5100	0.51	0.97	16.25
3	23	6900	0.71	0.92	15.83
4	20	6000	0.64	0.91	15.89
5	17	5100	0.73	0.94	15.88
6	16	4800	0.81	0.87	15.80
7	8	2400	0.67	0.93	16.50
8	22	6600	0.58	0.97	15.48
9	13	3900	0.38	0.94	15.80
10	19	5700	0.64	0.97	15.99
11	9	2700	0.44	0.97	15.91
12	22	6600	0.73	0.95	15.80
13	12	3600	0.38	0.94	15.78
14	13	3900	0.44	0.97	15.65
15	15	4500	0.81	0.86	15.82
16	14	4200	0.58	0.91	16.29
17	13	3900	0.71	0.84	16.26
18	19	5700	0.61	0.89	16.49
19	14	4200	0.51	0.86	16.31
20	16	4800	0.58	0.92	15.90

The results of a sequence of 20 independent iterative simulation fits for μ_stop in a representative single subject (B) with D = 100 ms, showing the degree of robustness of the final estimated value. Each fit reiterates until no further significant improvement occurs, with the number of iterations and therefore trials (300 trials per iteration) varying stochastically in each case (the Iterations and Trials columns); the data derive from a total of 95,400 trials; the mean estimate of μ_stop is 15.98 Hz (SEM=  0.06). p(K–S)_A and p(K–S)_B are the significance values for the resultant K–S tests in each case for the A and B response distributions, respectively.