TABLE III.

Prior probability distributions used for Bayesian calculations. Each prior distribution is a bounded Gaussian described by the four parameters in this table. For each parameter, the upper and lower bounds were chosen to be wide enough so as to affect the final result only minimally. The mean was chosen to be the midpoint between the upper and lower bounds, and the standard deviation was chosen to be one half of the difference between the upper and lower bound.

Parameter	Lower bound	Upper bound	Mean	Standard deviation
$A_{\text{fast}}$	0	1.0	0.5	0.5
$A_{\text{slow}}$	0	1.0	0.5	0.5
$v_{\text{fast}}\left(\frac{\mathrm{m}}{\mathrm{s}}\right)$	1500	3000	2250	750
$v_{\text{slow}}\left(\frac{\mathrm{m}}{\mathrm{s}}\right)$	800	2300	1550	750
${\beta }_{\text{fast}}\left(\frac{\text{dB}}{\text{cm}\cdot \text{MHz}}\right)$	0	86.9	43.4	43.4
${\beta }_{\text{slow}}\left(\frac{\text{dB}}{\text{cm}\cdot \text{MHz}}\right)$	0	86.9	43.4	43.4