Maximum Likelihood Estimates for the Parameters of Mixture Distributions
K. Malcolm Leytham · Water Resources Research · 1984
Maximum likelihood estimates for the parameters of a mixture of two normal distributions are presented in terms of an expectation‐maximization algorithm. Small sample properties of the parameter estimates are explored using Monte Carlo simulation. Although parameters estimated from unclassified data are inaccurate, quantiles derived from the fitted distributions are only slightly less accurate than quantiles estimated from classified data.