SuperGauss

Superfast Likelihood Inference for Stationary Gaussian Time Series

Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson 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 Durbin-Levinson around n = 300. Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.

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Description file content

Package
SuperGauss
Type
Package
Title
Superfast Likelihood Inference for Stationary Gaussian Time Series
Version
1.0.1
Date
2019-03-12
Description
Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson 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 Durbin-Levinson around n = 300. Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.
License
GPL-3
Depends
R (>= 3.0.0)
Imports
stats, methods, Rcpp (>= 0.12.7), fftw
LinkingTo
Rcpp, RcppEigen
Suggests
knitr, rmarkdown, testthat, mvtnorm, numDeriv
VignetteBuilder
knitr
RoxygenNote
6.1.1
Encoding
UTF-8
SystemRequirements
fftw3 (>= 3.1.2)
NeedsCompilation
yes
Packaged
2019-03-12 18:18:10 UTC; mlysy
Author
Yun Ling [aut], Martin Lysy [aut, cre]
Maintainer
Martin Lysy
Repository
CRAN
Date/Publication
2019-03-12 22:36:08 UTC

install.packages('SuperGauss')

1.0.1

2 months ago

Martin Lysy

GPL-3

Depends on

R (>= 3.0.0)

Imports

stats, methods, Rcpp (>= 0.12.7), fftw

Suggests

knitr, rmarkdown, testthat, mvtnorm, numDeriv

Discussions