Quasi-Continuous Maximum Entropy Distribution Approximation with Kernel Density

This paper extends maximum entropy estimation of discrete probabilitydistributions to the continuous case. This transition leads to a nonparametricestimation of a probability density function, preserving the maximumentropy principle. Furthermore, the derived density estimate providesa minimum mean integrated square error.[...]

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Year of publication:	2010-01-26
Authors:	Mazzoni, Thomas ; Reucher, Elmar
Institutions:	Fernuniversität <Hagen> / Fachbereich Wirtschaftswissenschaft / Lehrstuhl für Angewandte Statistik und Methoden der empirischen Sozialforschung
Subject:	Wahrscheinlichkeitsverteilung \| Entscheidungstheorie \| decision theory \| Dichteschätzung \| Kernel Density Estimation \| Maximum-Entropie-Methode \| Maximum Entropy Method

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1. Introduction
2. Milestones in Artificial Intelligence
3. Knowledge Acquisition by MaxEnt
4. Explorative Density Approximation
4.1. Nonparametric Density Approximation
4.2. Mimetic Hyperbolic Kernel Function
4.3. Efficiency of the Hyperbolic Kernel Function
5. Maximum Entropy and Boundary Conditions
5.1. Lagrange-Method for Constrained Optimization
5.2. Uniform and Normal Distribution Example
6. Maximum Entropy Density Approximation ofIncome under Constraints
7. Conclusions
References

Persistent link: https://www.econbiz.de/10005869750