# Estimating Parameters in Mathematical Model for Societal Booms through Bayesian Inference Approach

## TL;DR

This paper uses Bayesian inference to estimate parameters in a mathematical model of societal booms, validating its ability to capture real-world boom and bust dynamics through data fitting.

## Contribution

It introduces a Bayesian parameter estimation method for a societal boom model and demonstrates its effectiveness with actual data fitting.

## Key findings

- Model accurately fits transient and resurgent boom data
- Bayesian inference effectively estimates model parameters
- Model captures societal boom dynamics

## Abstract

In this study, based on our previous study, we examined the mathematical properties, especially the stability of the equilibrium for our proposed mathematical model. By means of the results of the stability in this study, we also used actual data representing transient booms and resurgent booms, and conducted parameter estimation for our proposed model using Bayesian inference. In addition, we conducted a model fitting to five actual data. By this study, we reconfirmed that we can express the resurgences or minute vibrations of actual data by means of our proposed model.