Measuring the relative effectiveness of moment estimators as starting values in maximizing likelihoods

DOI10.1016/0167-9473(94)90145-7zbMath0937.62532OpenAlexW2065209812MaRDI QIDQ1361505

W. David Furman, Bruce G. Lindsay

Publication date: 25 August 1997

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(94)90145-7

zbMATH Keywords

maximum likelihood estimationdeterminantsmixture of normal distributionsstarting valuesmoment matrices

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (8)

Testing for the number of components in a mixture of normal distributions using moment estimators ⋮ Mixture Model Analysis of Partially Rank‐Ordered Set Samples: Age Groups of Fish from Length‐Frequency Data ⋮ Choosing initial values for the EM algorithm for finite mixtures ⋮ Mixture Models, Robustness, and the Weighted Likelihood Methodology ⋮ Fitting Mixture Distributions Using Generalized Lambda Distributions and Comparison with Normal Mixtures ⋮ Separating a mixture of two normals with proportional covariances ⋮ Estimation of the income distribution and detection of subpopulations: an explanatory model ⋮ A global algorithm to estimate the expectations of the components of an observed univariate mixture

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• Consistency of the Maximum Likelihood Estimator in the Presence of Infinitely Many Incidental Parameters
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• Mixture Models, Outliers, and the EM Algorithm
• Estimation in Mixtures of Two Normal Distributions
• Estimating the components of a mixture of normal distributions
• Some Comparisons of the Method of Moments and the Method of Maximum Likelihood in Estimating Parameters of a Mixture of Two Normal Densities

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