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Maximum Likelihood Estimates for the Parameters of Mixture Distributions
Author(s) -
Leytham K. M.
Publication year - 1984
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr020i007p00896
Subject(s) - quantile , maximum likelihood , monte carlo method , expectation–maximization algorithm , statistics , mathematics , restricted maximum likelihood , statistical physics , physics
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.