Semiparametric inference on the means of multiple nonnegative distributions with excess zero observations

DOI10.1016/j.jmva.2018.02.010zbMath1499.62184OpenAlexW2789291040WikidataQ130096529 ScholiaQ130096529MaRDI QIDQ1749991

Paul Marriott, Chunlin Wang, Peng-Fei Li

Publication date: 17 May 2018

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10012/13382

zbMATH Keywords

empirical likelihoodestimating equationmultinomial logistic regressiondensity ratio modelnon-standard mixture modelsemi-continuous data

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Nonparametric estimation (62G05) Hypothesis testing in multivariate analysis (62H15)

Related Items (5)

A semiparametric marginalized zero-inflated model for analyzing healthcare utilization panel data with missingness ⋮ Statistical inference for a relaxation index of stochastic dominance under density ratio model ⋮ Semiparametric inference on general functionals of two semicontinuous populations ⋮ Density ratio model with data-adaptive basis function ⋮ Semiparametric empirical likelihood inference with estimating equations under density ratio models

Uses Software

• R
• GFD

Cites Work

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• Statistical inference for the common mean of two log-normal distributions and some applications in reliability
• Weighted empirical likelihood inference for multiple samples
• Empirical likelihood and general estimating equations
• Empirical likelihood-based confidence intervals for data with possible zero observations.
• Testing homogeneity for multiple nonnegative distributions with excess zero observations
• Empirical likelihood inference for two-sample problems
• On empirical likelihood for semiparametric two-sample density ratio models
• Using logistic regression for semiparametric comparison of population means and variances
• Hypothesis Tests for Point-Mass Mixture Data with Application to `Omics Data with Many Zero Values
• Hypothesis testing in the presence of multiple samples under density ratio models
• Multivariate logistic compounds
• A goodness-of-fit test for logistic regression models based on case-control data
• Box-Type Approximations in Nonparametric Factorial Designs
• Empirical likelihood confidence intervals for the mean of a population containing many zero values
• Comparison of Several Independent Population Means When Their Samples Contain Log‐Normal and Possibly Zero Observations
• On the Differential Geometry of the Wald Test with Nonlinear Restrictions
• Using covariate-specific disease prevalence information to increase the power of case-control studies
• Analysis of unbalanced factorial designs with heteroscedastic data
• Asymptotic Permutation Tests in General Factorial Designs
• Density ratio model selection
• Empirical likelihood inference for a common mean in the presence of heteroscedasticity
• THE SIGNIFICANCE OF THE DIFFERENCE BETWEEN TWO MEANS WHEN THE POPULATION VARIANCES ARE UNEQUAL
• Interval estimation for the ratio in means of log-normally distributed medical costs with zero values.

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