Parameter: Journal of Statistics
Vol. 3 No. 1 (2023)

BAYESIAN MARKOV CHAIN MONTE CARLO SIMULATION OF NONLIENAR MODEL FOR INFECTIOUS DISEASES WITH QUARANTINE

Usman, Ida (Unknown)

Article Info

Publish Date
30 Jun 2023

Abstract

The SIQS (Susceptible, Infective, Quarantine, and Susceptible) non-linear model is used to describe the dynamics of infectious diseases, especially optimizing individuals who are quarantined. Discretization of the SIQS model using the Runge-Kutta method and its physical interpretation is very useful if the model parameters can be estimated. Bayesian Markov Chain Monte Carlo for its numerical simulation. After 10,000 iterations, convergent and significant parameters were obtained, namely beta = 94.37, beta0 = -10.19, mu = -0.23 and b = 0.5.

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Journal Info
Parameter: Journal of Statistics
Website

Abbrev

parameter

Publisher

Universitas Tadulako

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

Description

Parameter: Journal of Statistics is a refereed journal committed to original research articles, reviews and short communications of Statistics and its ...