The label switching problem is caused by the likelihood of a Bayesian mixture model being invariant to permutations of the labels. The permutation can change multiple times between Markov Chain Monte Carlo (MCMC) iterations making it difficult to infer component-specific parameters of the model. Various so-called ‘relabelling’ strategies exist with the goal to ‘undo’ the label switches that hav...

'Multiple causation' is the canon of contemporary epidemiology, and its metaphor and model is the 'web of causation.' First articulated in a 1960 U.S. epidemiology textbook, the 'web' remains a widely accepted but poorly elaborated model, reflecting in part the contemporary stress on epidemiologic methods over epidemiologic theories of disease causation. This essay discusses the origins, featur...

In this paper, we present a minimal connection model of abductive diagnostic reasoning. The domain knowledge is represented by a causal network. An explanation of a set of observations is a chain of causation events. These causation events constitute a scenario where all the observations can be observed. We define the best explanation to be the most probable explanation. The underlying causal m...

The paper reviews what has come to be called the Rubin-Holland model of causation. That model takes as its starting point experimentation and defines causation as a hypothetical value: a difference score between the observation of a unit in control and experimental condition. We discuss several different implementations of the model that Rubin and Holland have suggested. We present several othe...

Circular causation epistemic outlook and model to address the interactively integrated ever-learning sustainability perspectives in every issue problem of socio-scientific extensiveness is a novel abstracto-empirical field contrast economic econometric theory all these aspects. The ensuing episteme substantive circular are introduced. unity knowledge shown be centerpiece problems that methodolo...