Theoretical analysis of power in a two-component normal mixture model

DOI10.1016/j.jspi.2004.04.003zbMath1066.62031OpenAlexW2009049722MaRDI QIDQ2485978

Michael Stewart, Hall, Peter

Publication date: 5 August 2005

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2004.04.003

zbMATH Keywords

Gaussian mixturePitman alternativeAsymptotic distributionLocal alternativeCritical phenomenonExtreme-value theoryLikelihood-ratio testNull hypothesis

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Asymptotic properties of parametric tests (62F05)

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Test for homogeneity in gamma mixture models using likelihood ratio, Mixture models: building a parameter space, Hypothesis test for normal mixture models: the EM approach, TESTING FOR HOMOGENEITY IN MIXTURE MODELS, Asymptotic distribution and local power of the likelihood ratio test for mixtures: bounded and unbounded cases, Detection boundary for a sparse gamma scale mixture model, Aggregated tests based on supremal divergence estimators for non-regular statistical models, Recent asymptotic results in testing for mixtures, Local score tests in mixture exponential family with fixed mean, The likelihood ratio test for general mixture models with or without structural parameter

Cites Work

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• Extremes and related properties of random sequences and processes
• Weighted empirical and quantile processes
• The distribution of the likelihood ratio for mixtures of densities from the one-parameter exponential family
• Asymptotics for likelihood ratio tests under loss of identifiability
• Likelihood ratio inequalities with applications to various mixtures
• Asymptotics for the likelihood ratio test in a two-component normal mixture model
• Likelihood ratio tests based on subglobal optimization: A power comparison in exponential mixture models
• Simulated Percentage Points for the Null Distribution of the Likelihood Ratio Test for a Mixture of Two Normals
• Hypothesis Testing When a Nuisance Parameter is Present Only Under the Alternative
• Testing in locally conic models, and application to mixture models
• Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case
• Estimating the components of a mixture of normal distributions
• A cautionary note on likelihood ratio tests in mixture models
• Likelihood ratio test for univariate Gaussian mixture