in the proper motion diagram or VPD (top left) and several colour-magnitude sub-spaces (K versus (i-K), i versus (i-K), and K versus (r-K), from top right to bottom left clockwise).

   $\mu_{\alpha}$   $\mu_{\delta}$      u         g         r        i        Z        Y        J        H        K
  ---------------- ---------------- --------- --------- --------- -------- -------- -------- -------- -------- --------
         0                0          1842682   1627728   1294168   928902   725393   724041   601758   746009   768222

We used an initial list of Pleiades candidate members [derived from @2007ApJS..172..663S] as the starting point for the derivation of our models. We will refer to this initial list as the initial reference set.

Methodology
-----------

The approach adopted here consists of inferring the posterior membership probability given the observations $\mathcal{D}$, $p({\cal
  C}|{\cal D})$, using Bayes’ theorem (Eq. \[bayes.th\]).

In Eq. \[bayes.th\], the posterior membership probability (the left-hand side) is expressed in terms of the likelihood ($p(D|{\cal
  C})$) and the prior probabilities ($p({\cal C})$ and $p({\cal
  D})$). We define the prior membership probability as the proportion of cluster members in the entire data set.

In addition to the prior probabilities, a mathematical model of the likelihood is needed to convert prior into posterior probabilities. In the following paragraphs we explain our strategies to derive the likelihood function.

