3 papers
stat.ME2021
Bayesian mixture autoregressive model with Student's t innovations
Davide Ravagli, Georgi N. Boshnakov
This paper introduces a fully Bayesian analysis of mixture autoregressive models with Student t components. With the capacity of capturing the behaviour in the tails of the distrib…
stat.ME2021
A signed power transformation with application to white noise testing
Georgi N. Boshnakov, Davide Ravagli
We show that signed power transforms of some ARCH-type processes give ARCH-type processes. The class of ARCH-type models for which this property holds contains many common ARCH and…
stat.ME2020
Bayesian analysis of mixture autoregressive models covering the complete parameter space
Davide Ravagli, Georgi N. Boshnakov
Mixture autoregressive (MAR) models provide a flexible way to model time series with predictive distributions which depend on the recent history of the process and are able to acco…