An approach to produce a model for the data generating distribution is the well-known maximum entropy method. In this approach, the partial knowledge about the data generating distribution is formulated in terms of a set of information constraints, usually moment constraints, and the inference is based on the model that maximizes Shannon’s entropy under these constraints. In this paper we inves...

Analytical studies of evolutionary processes based on the demographic parameter entropy-a measure of the uncertainty in the age of the mother of a randomly chosen newborn-show that evolutionary changes in entropy are contingent on environmental constraints and can be characterized in terms of three tenets: (i) a unidirectional increase in entropy for populations subject to bounded growth constr...

For each transition probability, MEMM uses maximum entropy model. Maximum entropy model is used to model the data distribution, which gives us as much information as possible. Without any constraints, the uniform distribution gives us maximum entropy. However, we have training data which gives some facts about the true distribution. What maximum entropy model does is to maximize the entropy of ...

Traditionally, the Method of (Shannon-Kullback’s) Relative Entropy Maximization (REM) is considered with linear moment constraints. In this work, the method is studied under frequency moment constraints which are non-linear in probabilities. The constraints challenge some justifications of REM since a) axiomatic systems are developed for classical linear moment constraints, b) the feasible set ...

In this paper, we discuss a multiperiod portfolio selection problem with fuzzy returns. We present a new credibilitic multiperiod mean semi- absolute deviation portfolio selection with some real factors including transaction costs, borrowing constraints, entropy constraints, threshold constraints and risk control. In the proposed model, we quantify the investment return and risk associated with...

The application of the Maximum Entropy (ME) principle leads to a minimum of the Mutual Information (MI), I(X,Y), between random variables X,Y, which is compatible with prescribed joint expectations and given ME marginal distributions. A sequence of sets of joint constraints leads to a hierarchy of lower MI bounds increasingly approaching the true MI. In particular, using standard bivariate Gaus...

We use Big Bang Nucleosynthesis (BBN) data in order to impose constraints on the exponent of Barrow entropy. The latter is an extended entropy relation arising from incorporation quantum-gravitational effects black-hole structure, parameterized effectively by new parameter $\Delta$. When considered a cosmological framework and under light gravity-thermodynamics conjecture, leads modified scenar...

in this paper, we consider the determination methods of maximum entropy multivariate distributions with given prior under the constraints, that the marginal distributions or the marginals and covariance matrix are prescribed. next, some numerical solutions are considered for the cases of unavailable closed form of solutions. finally, these methods are illustrated via some numerical examples.