Conditional Independence in Statistical Theory 论文

1979Journal of the Royal Statistical Society Series B (Statistical Methodology)引用 1541
DOI
Statistical Methods and InferenceAdvanced Causal Inference TechniquesBayesian Modeling and Causal Inference
Statistical Methods and InferenceBayesian Modeling and Causal InferenceAdvanced Causal Inference Techniques
相关技术:Bayesian Modeling and Causal InferenceAdvanced Causal Inference TechniquesStatistical Methods and Inference
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Summary Some simple heuristic properties of conditional independence are shown to form a conceptual framework for much of the theory of statistical inference. This framework is illustrated by an examination of the rôle of conditional independence in several diverse areas of the field of statistics. Topics covered include sufficiency and ancillarity, parameter identification, causal inference, prediction sufficiency, data selection mechanisms, invariant statistical models and a subjectivist approach to model-building.

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A. P. Dawid

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Bayesian Modeling and Causal InferenceAdvanced Causal Inference TechniquesStatistical Methods and Inference

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