Quotation Bitto-Nemling, Angela, Frühwirth-Schnatter, Sylvia. 2018. Time Varying Parameter Mixture Model. Computational Statistics and Molecular Simulation: A Practical Cross-Fertilization, BIRS-CMO, Mexico, 11.11.-16.11. Invited Talk




We introduce the TVP (Time Varying Parameter) Mixture Model. Based on previous work (Bitto and Fruehwirth-Schnatter, 2017), the focus of this paper is the estimation of a time-varying parameter model with shrinkage priors. The key idea is the usage of spike-and-slab priors for the process variances. We assume that both spike and slab have a hierarchical representation as a normal-gamma prior (Griffin and Brown,2010). In this way we extend previous work based on spike-and-slab priors (Frühwirth-Schnatter and Wagner, 2010) and Bayesian Lasso type priors (Belmonte et al. 2014). We present necessary modifications of our efficient MCMC estimation scheme, exploiting ideas such as ancillarity-sufficiency interweaving (Yu and Meng, 2011). We present our idea with a simulation study.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title Time Varying Parameter Mixture Model
Event Computational Statistics and Molecular Simulation: A Practical Cross-Fertilization
Year 2018
Date 11.11.-16.11.
Country Mexico
Location BIRS-CMO
URL https://www.birs.ca/events/2018/5-day-workshops/18w5023/schedule
Invited Talk Y


Bitto-Nemling, Angela (Former researcher)
Frühwirth-Schnatter, Sylvia (Details)
Institute for Statistics and Mathematics IN (Details)
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