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Bayesian Propositional Logic

100%

Jarmużek T., Klonowski M., Malinowski J.

Bulletin of the Section of Logic

2017

tom 46

nr 3/4

We define and investigate from a logical point of view a family of consequence relations defined in probabilistic terms. We call them relations of supporting, and write: |≈w where w is a probability function on a Boolean language. A |≈w B iff the fact that A is the case does not decrease a probability of being B the case. Finally, we examine the intersection of |≈w , for all w, and give some formal properties of it.

Inference for copula modeling of discrete data: a cautionary tale and some facts

100%

Faugeras O. P.

Dependence Modeling

2017

tom 5

nr 1

121-132

In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula models. For the latter, we stress, among other issues, the possibility of obtaining impossible models, arising from model misspecification or unidentifiability of the copula parameter.

Ograniczanie wyników

1 Bulletin of the Section of Logic

1 Dependence Modeling

1 Faugeras O. P.

1 Jarmużek T.

1 Klonowski M.

1 Malinowski J.

2 2017

Wyniki wyszukiwania

Bayesian Propositional Logic

Inference for copula modeling of discrete data: a cautionary tale and some facts