The Joint Distribution of the Discrete Random Set Vector and Bivariate Coarsening at Random Models

DOI10.1007/978-3-030-45619-1_19zbMath1451.62174OpenAlexW3037209726MaRDI QIDQ5126385

Tonghui Wang, Zheng Wei, Baokun Li

Publication date: 16 October 2020

Published in: Statistical and Fuzzy Approaches to Data Processing, with Applications to Econometrics and Other Areas (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-45619-1_19

zbMATH Keywords

copularandom setcoarsening at random modeljoint belief functionjointly monotone of infinite order

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistical aspects of big data and data science (62R07)

Cites Work

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• Characterizing joint distributions of random sets by multivariate capacities
• Semiparametric theory and missing data.
• Ignorability for categorical data
• Improved Doubly Robust Estimation When Data Are Monotonely Coarsened, with Application to Longitudinal Studies with Dropout
• The Joint Belief Function and Shapley Value for the Joint Cooperative Game
• An Introduction to Random Sets
• Theory of Random Sets
• Upper and Lower Probabilities Induced by a Multivalued Mapping

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