Kernel smoothing density estimation when group membership is subject to missing

DOI10.1016/J.JSPI.2011.09.009zbMath1227.62020OpenAlexW2054753144WikidataQ35564963 ScholiaQ35564963MaRDI QIDQ651072

Hua He, Douglas Gunzler, Wan Tang

Publication date: 8 December 2011

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

Full work available at URL: http://europepmc.org/articles/pmc3221313

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (4)

Prediction model-based kernel density estimation when group membership is subject to missing ⋮ On density and regression estimation with incomplete data ⋮ Distribution-free inference of zero-inflated binomial data for longitudinal studies ⋮ Doubly robust kernel density estimation when group membership is missing at random

Uses Software

• KernSmooth

Cites Work

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• Smoothing methods in statistics
• Probability density estimation with data missing at random when covariables are present
• Semiparametric theory and missing data.
• Semiparametric Efficiency in Multivariate Regression Models with Missing Data
• Estimating disease prevalence in two-phase studies
• On Estimation of a Probability Density Function and Mode
• Doubly Robust Estimation of the Area Under the Receiver-Operating Characteristic Curve in the Presence of Verification Bias
• A Generalization of Sampling Without Replacement From a Finite Universe
• Maximum Likelihood Estimation of Misspecified Models

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