Index B | C | H | L | M | N | O | P | T | W B Bayesian methods C credible intervals H homoscedastic L likelihood M Markov chain Monte Carlo maximum likelihood estimation model dataset N nested sampling normal distribution O optimisation algorithm P parameters posterior distribution prior knowledge T thinning W walkers