Likelihood evaluations for stationary Gaussian time series are typically obtained via the DurbinLevinson algorithm, which scales as O(n^2) in the number of time series observations. This package provides a "superfast" O(n log^2 n) algorithm written in C++, crossing over with DurbinLevinson around n = 300. Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as NewtonRaphson and Hamiltonian Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a headeronly library, to simplify lowlevel usage in other packages and outside of R.
Package details 


Author  Yun Ling [aut], Martin Lysy [aut, cre] 
Date of publication  20170705 23:00:36 UTC 
Maintainer  Martin Lysy <[email protected]> 
License  GPL3 
Version  1.0 
Package repository  View on CRAN 
Installation 
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