Discrete approximations of continuous distributions by maximum entropy

C-Tier
Journal: Economics Letters
Year: 2013
Volume: 118
Issue: 3
Pages: 445-450

Authors (2)

Tanaka, Ken’ichiro (not in RePEc) Toda, Alexis Akira (Emory University)

Score contribution per author:

0.503 = (α=2.01 / 2 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

In numerically implementing the optimization of an expected value in many economic models, it is often necessary to approximate a given continuous probability distribution by a discrete distribution. We propose an approximation method based on the principle of maximum entropy and minimum Kullback–Leibler information, which is computationally very simple. Our method is not intended to replace existing methods but to complement them by “fine-tuning” probabilities so as to match prescribed (not necessarily polynomial) moments exactly.

Technical Details

RePEc Handle
repec:eee:ecolet:v:118:y:2013:i:3:p:445-450
Journal Field
General
Author Count
2
Added to Database
2026-01-29