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Bayesian dynamic regression models where the regression coefficients can vary over time as random walks. Gaussian, Poisson, and binomial observations are supported. The Markov chain Monte Carlo computations are done using Hamiltonian Monte Carlo provided by Stan, using a state space representation of the model in order to marginalise over the coefficients for efficient sampling.
Package details 


Author  Jouni Helske 
Date of publication  20170712 14:26:08 UTC 
Maintainer  Jouni Helske <[email protected]> 
License  GPL (>= 2) 
Version  0.2.0 
Package repository  View on CRAN 
Installation 
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