Package: SuperGauss
Type: Package
Title: Superfast Likelihood Inference for Stationary Gaussian Time
        Series
Version: 2.0.4
Date: 2025-09-09
Authors@R: c(person("Yun", "Ling", role = "aut"),
             person("Martin", "Lysy",
	            email = "mlysy@uwaterloo.ca",
		    role = c("aut", "cre")))
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.
URL: https://github.com/mlysy/SuperGauss
BugReports: https://github.com/mlysy/SuperGauss/issues
License: GPL-3
Depends: R (>= 3.0.0)
Imports: stats, methods, R6, Rcpp (>= 0.12.7), fftw
LinkingTo: Rcpp, RcppEigen
Suggests: knitr, rmarkdown, testthat, mvtnorm, numDeriv
VignetteBuilder: knitr
RoxygenNote: 7.3.2
Roxygen: list(markdown = TRUE)
Encoding: UTF-8
SystemRequirements: fftw3 (>= 3.1.2)
Config/pak/sysreqs: libfftw3-dev
Repository: https://mlysy.r-universe.dev
Date/Publication: 2025-09-09 17:26:16 UTC
RemoteUrl: https://github.com/mlysy/supergauss
RemoteRef: HEAD
RemoteSha: eca63a3422067c3932953e5db4d01732cc4326a5
NeedsCompilation: yes
Packaged: 2026-06-24 04:56:16 UTC; root
Author: Yun Ling [aut],
  Martin Lysy [aut, cre]
Maintainer: Martin Lysy <mlysy@uwaterloo.ca>