Inference for a two-component mixture of symmetric distributions under log-concavity

DOI10.3150/16-BEJ864zbMath1419.62059arXiv1411.4708OpenAlexW2963406788MaRDI QIDQ2405213

Fadoua Balabdaoui, Charles R. Doss

Publication date: 21 September 2017

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1411.4708

zbMATH Keywords

mixtureconsistencyempirical processessymmetricglobal ratebracketing entropyHellinger metriclog-concave

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05)

Related Items (14)

The robust EM-type algorithms for log-concave mixtures of regression models ⋮ Flexible families of symmetric and asymmetric distributions based on the two-piece skew normal distribution ⋮ An EM algorithm for fitting a mixture model with symmetric log-concave densities ⋮ Inference for Local Parameters in Convexity Constrained Models ⋮ Maximum likelihood estimation of the log-concave component in a semi-parametric mixture with a standard normal density ⋮ Recent progress in log-concave density estimation ⋮ Semiparametric density testing in the contamination model ⋮ High-dimensional nonparametric density estimation via symmetry and shape constraints ⋮ An overview of semiparametric extensions of finite mixture models ⋮ Minimum Hellinger distance estimation for a semiparametric location-shifted mixture model ⋮ A semiparametric mixture method for local false discovery rate estimation from multiple studies ⋮ A Bayesian nonparametric approach to log-concave density estimation ⋮ Semiparametric mixture regression with unspecified error distributions ⋮ Univariate log-concave density estimation with symmetry or modal constraints

Uses Software

• R
• logcondens.mode

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