suspected the chain had not sampled the posterior probability distribution accurately we calculated a new Markov Chain starting from the best-fit parameters in the previous chain and using an increased number of chain steps and/or an increased number of walkers with a large spread of initial parameter values to ensure convergence. The standard error per observation was either assumed to be constant for all the data, or assumed to be constant within each of two blocks of data where there is a gap in the observations. These values of the standard error were included as free parameters in the MCMC analysis by including the necessary term in the calculation of the likelihood for each chain step. Unless otherwise stated, we only use data within a range of 1.5 times the eclipse width (as listed in Table \[lcinfo\]) centred on each eclipse in this analysis. This ensures that these standard error estimates (and, hence, the error estimates on the model parameters) are determined by the scatter in the residuals through the eclipse, rather than the much lower scatter in the residuals between the eclipses. From preliminary fits to the complete light curves we found that the out-of-eclipse level is always very 