Quotation Kastner, Gregor. 2017. factorstochvol: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models.


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Abstract

Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility models. Sparsity can be achieved through the usage of Normal-Gamma priors on the factor loading matrix.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Software
Title factorstochvol: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models
Date Jan. 1, 2017
Version 0.8.3
Licence GPL-2 | GPL-3
Operating system Linux, Windows, OS X
Language English
Programming language R, C, C++

Associations

People
Kastner, Gregor (Details)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1105 Computer software (Details)
1162 Statistics (Details)
5323 Econometrics (Details)
5701 Applied statistics (Details)
5707 Time series analysis (Details)
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