A Note on the Relationship Between Conditional and Unconditional Independence, and its Extensions for Markov Kernels
Statistics Theory
2021-10-28 v2 Statistics Theory
Abstract
Two known results on the relationship between conditional and unconditional independence are obtained as a consequence of the main result of this paper, a theorem that uses independence of Markov kernels to obtain a minimal condition which added to conditional independence implies independence. Some counterexamples and representation results are provided to clarify the concepts introduced and the propositions of the statement of the main theorem. Moreover, conditional independence and the mentioned results are extended to the framework of Markov kernels.
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Cite
@article{arxiv.1706.03955,
title = {A Note on the Relationship Between Conditional and Unconditional Independence, and its Extensions for Markov Kernels},
author = {A. G. Nogales and P. Pérez},
journal= {arXiv preprint arXiv:1706.03955},
year = {2021}
}
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12 pages