Table D.1.
Fit parameters from a Bayesian linear regression to all clusters in the upper two panels of Fig. 2.
| slope | intercept | |
|---|---|---|
| km/s/pc | km/s | |
| U vs. X | 0.031 ± 0.005 | -8.927 ± 0.610 |
| V vs. Y | 0.040 ± 0.002 | -17.721 ± 0.095 |
Notes. The Bayesian linear regression returns a posterior probability distribution for each fitting parameter; we call them “slope” and “intercept” for the linear fit. The parameter value and its uncertainty are computed as the median and median absolute deviation of the posterior probability distribution, respectively.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.