This method can be employed to determine parameter estimates for a distribution (see Quantile-Quantile Plots, Probability-Probability Plots, and Process Analysis). The method of matching moments sets the distribution moments equal to the data moments and solves to obtain estimates for the distribution parameters. For example, for a distribution with two parameters, the first two moments of the distribution (the mean and variance of the distribution, respectively, e.g., m and s, respectively) would be set equal to the first two moments of the data (the sample mean and variance, respectively, e.g., the unbiased estimators x-bar and s2, respectively) and solved for the parameter estimates. Alternatively, you could use the Maximum Likelihood Method to estimate the parameters. For more information, see Hahn and Shapiro, 1994.