# r2_is n=400 nsamples=150000 seed=401 imax=24000; mean C = 1.99199 (2-2/n = 1.99500); walks absorbed before imax: 0
# columns: label i  r=E N_i e^{i/n}  SE  relSE  e^{-y^2/2 or -i^2/(2n^3)}  E N_i e^{i/n+i^2/(2n^3)}  heuristic (1-i/n^2)^n e^{i/n}
y=0.25 2000 0.977415 1.83e-04 1.88e-04 0.969233 1.008441 0.968978
y=0.50 4000 0.893331 1.80e-04 2.01e-04 0.882497 1.012277 0.880625
y=1.00 8000 0.611233 1.44e-04 2.35e-04 0.606531 1.007753 0.596117
y=1.50 12000 0.316495 9.07e-05 2.87e-04 0.324652 0.974874 0.305863
y=2.00 16000 0.122127 4.29e-05 3.52e-04 0.135335 0.902404 0.117161
y=3.00 24000 0.007031 3.56e-06 5.06e-04 0.011109 0.632903 0.006687
x=0.5 200 1.002473 1.90e-04 1.89e-04 0.999688 1.002787 0.999687
x=1.0 400 1.002243 1.88e-04 1.88e-04 0.998751 1.003496 0.998749
x=2.0 800 1.000215 1.80e-04 1.80e-04 0.995012 1.005229 0.994996
x=4.0 1600 0.987590 1.81e-04 1.83e-04 0.980199 1.007541 0.980067
x=8.0 3200 0.933185 1.86e-04 1.99e-04 0.923116 1.010907 0.922117
x=16.0 6400 0.735283 1.58e-04 2.14e-04 0.726149 1.012579 0.719789
# sum_{i<=imax} E N_i = 399.000000 (n-1 = 399);  mean excursion length sum i E N_i/(n-1) = 399.9961 (n = 400; rel dev -9.70e-06)
# sum_{i>=1} |E N_i - e^{-i/n}| (i<=imax, plus e^{-i/n} tail 3.50e-24) = 2.1748  [upward-biased by MC noise]
