A point on discrete versus continuous state-space Markov chains
Location
Room 321, Hume Hall
Start Date
27-4-2024 10:00 AM
End Date
27-4-2024 11:00 AM
Description
In this poster, I will explore the impact of discrete marginals on copula-based Markov chains. We analyze the mixing properties of such models to emphasize the difference between continuous and discrete state-space Markov chains. The Maximum likelihood approach is applied to derive estimators for model parameters in the case of a discrete-state space Markov chain with Bernoulli marginal distribution. A stationary case and a non-stationary case are considered. The asymptotic distributions of parameter estimators are provided. A simulation study showcases the performance of different estimators for the Bernoulli parameter of the marginal distribution. Some statistical tests are provided for model parameters.
Relational Format
conference proceeding
Recommended Citation
Muia, Mathias, "A point on discrete versus continuous state-space Markov chains" (2024). AMS-AWM Student Research Symposium. 6.
https://egrove.olemiss.edu/ams_awm_sympo/2024/schedule/6
A point on discrete versus continuous state-space Markov chains
Room 321, Hume Hall
In this poster, I will explore the impact of discrete marginals on copula-based Markov chains. We analyze the mixing properties of such models to emphasize the difference between continuous and discrete state-space Markov chains. The Maximum likelihood approach is applied to derive estimators for model parameters in the case of a discrete-state space Markov chain with Bernoulli marginal distribution. A stationary case and a non-stationary case are considered. The asymptotic distributions of parameter estimators are provided. A simulation study showcases the performance of different estimators for the Bernoulli parameter of the marginal distribution. Some statistical tests are provided for model parameters.
Comments
poster