Generalised Measures of Multivariate Information Content
نویسندگان
چکیده
منابع مشابه
Generalised information and entropy measures in physics
The formalism of statistical mechanics can be generalised by starting from more general measures of information than the Shannon entropy and maximising those subject to suitable constraints. We discuss some of the most important examples of information measures that are useful for the description of complex systems. Examples treated are the Rényi entropy, Tsallis entropy, Abe entropy, Kaniadaki...
متن کاملGeneralised Husimi Functions: Analyticity and Information Content
The analytic properties of a class of Generalised Husimi Functions are discussed, with particular reference to the problem of state reconstruction. The class consists of the subset of Wódkiewicz's operational probability distributions for which the filter reference state is a squeezed vacuum state. The fact that the function is analytic means that perfectly precise knowledge of its values over ...
متن کاملMultivariate information measures: an experimentalist's perspective
Information theory has long been used to quantify interactions between two variables. With the rise of complex systems research, multivariate information measures are increasingly needed. Although the bivariate information measures developed by Shannon are commonly agreed upon, the multivariate information measures in use today have been developed by many different groups, and differ in subtle,...
متن کاملDynamic Bayesian Information Measures
This paper introduces measures of information for Bayesian analysis when the support of data distribution is truncated progressively. The focus is on the lifetime distributions where the support is truncated at the current age t>=0. Notions of uncertainty and information are presented and operationalized by Shannon entropy, Kullback-Leibler information, and mutual information. Dynamic updatings...
متن کاملInformation Measures via Copula Functions
In applications of differential geometry to problems of parametric inference, the notion of divergence is often used to measure the separation between two parametric densities. Among them, in this paper, we will verify measures such as Kullback-Leibler information, J-divergence, Hellinger distance, -Divergence, … and so on. Properties and results related to distance between probability d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Entropy
سال: 2020
ISSN: 1099-4300
DOI: 10.3390/e22020216