In this paper, the continuous optimal control theory is used to model and solve the maximum entropy problem for a continuous random variable. The maximum entropy principle provides a method to obtain least-biased probability density function (Pdf) estimation. In this paper, to find a closed form solution for the maximum entropy problem with any number of moment constraints, the entropy is considered as a functional measure and the moment constraints are considered as the state equations. Therefore, the Pdf estimation problem can be reformulated as the optimal control problem. Finally, the proposed method is applied to estimate the Pdf of the hourly electricity prices of New England and Ontario electricity markets. Obtained results show the ...
Estimation of the probability density function from the statistical power moments presents a challen...
The determination of the probability distribution function (PDF) of uncertain input and model parame...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...
This article revisits the maximum entropy algorithm in the context of recovering the probability dis...
Recently we used the maximum entropy principle for finding the price density in a multi agent insura...
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (...
In this paper, we consider the newsvendor model under partial information, i.e., where the demand di...
Traditionally, the Method of (Shannon-Kullback's) Relative Entropy Maximization (REM) is considered ...
Abstract — There is a controversial debate about the effects of the promotion of renewable energy an...
Abstract:- Maximum entropy (MaxEnt) principle is a method for analyzing the available information in...
The maximum entropy method is a theoretically sound approach to construct an analytical form for the...
The maximum entropy method (maxent) is widely used in the context of the moment problem which appear...
In many practical situations, we have only partial information about the probabilities. In some case...
The determination of directional power density distribution of an electromagnetic wave from the elec...
Maximum entropy spectral density estimation is a technique for reconstructing an unknown density fun...
Estimation of the probability density function from the statistical power moments presents a challen...
The determination of the probability distribution function (PDF) of uncertain input and model parame...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...
This article revisits the maximum entropy algorithm in the context of recovering the probability dis...
Recently we used the maximum entropy principle for finding the price density in a multi agent insura...
We introduce a maximum entropy approach to parameter estimation for computable general equilibrium (...
In this paper, we consider the newsvendor model under partial information, i.e., where the demand di...
Traditionally, the Method of (Shannon-Kullback's) Relative Entropy Maximization (REM) is considered ...
Abstract — There is a controversial debate about the effects of the promotion of renewable energy an...
Abstract:- Maximum entropy (MaxEnt) principle is a method for analyzing the available information in...
The maximum entropy method is a theoretically sound approach to construct an analytical form for the...
The maximum entropy method (maxent) is widely used in the context of the moment problem which appear...
In many practical situations, we have only partial information about the probabilities. In some case...
The determination of directional power density distribution of an electromagnetic wave from the elec...
Maximum entropy spectral density estimation is a technique for reconstructing an unknown density fun...
Estimation of the probability density function from the statistical power moments presents a challen...
The determination of the probability distribution function (PDF) of uncertain input and model parame...
Abstract—In many practical situations, we have only partial information about the probabilities. In ...