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Found 5 papers, 1 papers with code
Resolution of Simpson's paradox via the common cause principle
Thus, for the minimal common cause, one should choose the option of Simpson's paradox that assumes conditioning over $B$ and not its marginalization.
The most likely common cause
We show that the generalized maximum likelihood method can be applied to this situation and allows identification of $C$ that is consistent with the common cause principle.
Maximum Entropy competes with Maximum Likelihood
Here we study MAXENT in a Bayesian decision theory set-up, i. e. assuming that there exists a well-defined prior Dirichlet density for unknown probabilities, and that the average Kullback-Leibler (KL) distance can be employed for deciding on the quality and applicability of various estimators.
Observational nonidentifiability, generalized likelihood and free energy
We study the parameter estimation problem in mixture models with observational nonidentifiability: the full model (also containing hidden variables) is identifiable, but the marginal (observed) model is not.
Rank-frequency relation for Chinese characters
The scenario of its validity is similar to the Zipf's law for words in short English texts.
