postMui {skipTrack} | R Documentation |
In our model the data are drawn from LogN(mu_i + log(c_ij), tau_i). The prior for mu_i is given as N(x_i^T %*% beta, rho). This function draws from the conditional posterior of mu_i.
postMui(yij, cij, taui, xib, rho)
yij |
Numeric vector, cycle lengths for a single individual |
cij |
Positive Integer vector, a sampled vector of length(yij) where the corresponding values in cij indicate a sampled number of TRUE cycles in each cycle length given by yij |
taui |
Numeric > 0, A sampled precision for the yijs |
xib |
Numeric, result of multiplying x_i^T %*% beta (single value, not vector) |
rho |
Numeric > 0, sampled prior precision of mu_i |
Additionally, note that in order to vectorize the remainder of the MCMC algorithm this function returns the sampled value repeated for length(yij)
Numeric vector, repeated sampled value of length(yij)