Generalized Functions & Experimental Methods of Obtaining Statistical Variable-Quantities Which Fully Determine Preferences in Choice-Rich Environments

TL;DR

This paper introduces a framework where preferences are modeled as distributions derived from generalized functions, linking economic decision models with physiological data for better understanding of choice behavior.

Contribution

It presents a novel approach connecting physiological observables with economic preferences, enabling comprehensive models without simplifying assumptions.

Findings

Preferences modeled as distributions from generalized functions

Physiological data can be visualized within economic models

Models align with physiological experiments and explain behavior

Abstract

Preferences of individuals are distributions of elements generated by generalized functions. Models of economic decision-making derived from such distributions are consistent with results of physiological experiments, and explain any behavioral situations without simplifying assumptions. Quantities in such models precisely correspond to experimentally obtainable physiological observables which determine statistical properties of central nervous system as it represents different stimuli. Graphical method of consistently and quantitatively at-a-glance interpreting or visualizing physiological data within context of economic models is demonstrated.