Mode hunting through active information

Daniel Andrés Díaz-Pachón; Juan Pablo Sáenz; Jonnagadda S Rao; Jean Eudes Dazard

doi:10.1002/asmb.2430

Mode hunting through active information

Daniel Andrés Díaz-Pachón, Juan Pablo Sáenz, Jonnagadda S Rao, Jean Eudes Dazard

Public Health Sciences

Research output: Contribution to journal › Article

1 Scopus citations

Abstract

We propose a new method to find modes based on active information. We develop an algorithm called active information mode hunting (AIMH) that, when applied to the whole space, will say whether there are any modes present and where they are. We show AIMH is consistent and, given that information increases where probability decreases, it helps to overcome issues with the curse of dimensionality. The AIMH also reduces the dimensionality with no resource to principal components. We illustrate the method in three ways: with a theoretical example (showing how it performs better than other mode hunting strategies), a real dataset business application, and a simulation.

Original language	English (US)
Journal	Applied Stochastic Models in Business and Industry
DOIs	https://doi.org/10.1002/asmb.2430
State	Published - Jan 1 2019

Keywords

active information
high dimensional
mode hunting

ASJC Scopus subject areas

Modeling and Simulation
Business, Management and Accounting(all)
Management Science and Operations Research

Access to Document

10.1002/asmb.2430

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Cite this

Díaz-Pachón, D. A., Sáenz, J. P., Rao, J. S., & Dazard, J. E. (2019). Mode hunting through active information. Applied Stochastic Models in Business and Industry. https://doi.org/10.1002/asmb.2430

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