Asymptotic Inference with Incomplete Data

DOI10.1080/03610926.2011.621577zbMath1277.62081OpenAlexW2076311020MaRDI QIDQ2865265

Keiji Takai, Yutaka Kano

Publication date: 29 November 2013

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2011.621577

zbMATH Keywords

incomplete datamaximum likelihood estimatormissing at randomasymptotic inferencenot missing at random

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20)

Related Items (9)

Effects of unlabeled data on classification error in normal discriminant analysis ⋮ A note on the properties of estimators in missing data analysis ⋮ Asymptotic comparison of semi-supervised and supervised linear discriminant functions for heteroscedastic normal populations ⋮ Impact of the non-distinctness and non-ignorability on the inference by multiple imputation in multivariate multilevel data: a simulation assessment ⋮ Unnamed Item ⋮ Kernel regression estimation for incomplete data with applications ⋮ On the use of the selection matrix in the maximum likelihood estimation of normal distribution models with missing data ⋮ Survival analysis of pension scheme mortality when data are missing ⋮ Bias reduction using surrogate endpoints as auxiliary variables

Cites Work

• Normal distribution based pseudo ML for missing data: with applications to mean and covariance structure analysis
• Inference and missing data
• Asymptotic Properties of Non-Linear Least Squares Estimators
• Linear Statistical Inference and its Applications
• Note on the Consistency of the Maximum Likelihood Estimate
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