En este trabajo se establece un criterio de comparación entre sistemas de información difusa basado en la maximización de la energía informacional esperada de orden α y tipo β y se comprueba que verifica las propiedades más relevantes que a nuestro juicio debe verificar un criterio de comparación.

In this paper the Kagan divergence measure is extended in order to establish a measure of the information that a random sample gives about a Dirichlet process as a whole. After studying some of its properties, the expression obtained in sampling from the step n to the step n+1 is given, and its Bayesian properties are studied. We finish proving the good behaviour of a stopping rule defined on the basis of the information obtained in sampling when passing from a step to the following.

We study Bayesian decision making based on observations $\left(X_{n,t}:t\in \{0,\frac{T}{n},2\frac{T}{n},...,n\frac{T}{n}\}\right)$ ($T>0,n\in \mathbb{N}$) of the discrete-time price dynamics of a financial asset, when the hypothesis a special $n$-period binomial model and the alternative is a different $n$-period binomial model. As the observation gaps tend to zero (i. e. $n\to \infty$), we obtain the limits of the corresponding Bayes risk as well as of the related Hellinger integrals and power divergences. Furthermore, we also give an example for the “non-commutativity” between Bayesian statistical and...