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author | Ricardo Wurmus <rekado@elephly.net> | 2019-12-13 18:56:39 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2019-12-13 22:41:40 +0100 |
commit | a8a7ba9acb5108f710a89e6e79c686ee5979c209 (patch) | |
tree | 6e1a1f6f5e59d43dfe98573af30d454fdcb18898 /gnu/packages | |
parent | 43a70edc291de476d705805230f61458de992f70 (diff) | |
download | guix-a8a7ba9acb5108f710a89e6e79c686ee5979c209.tar.gz guix-a8a7ba9acb5108f710a89e6e79c686ee5979c209.zip |
gnu: Add r-acfmperiod.
* gnu/packages/cran.scm (r-acfmperiod): New variable.
Diffstat (limited to 'gnu/packages')
-rw-r--r-- | gnu/packages/cran.scm | 29 |
1 files changed, 29 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 8c7fe23667..ece356e7cd 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -17022,3 +17022,32 @@ to maximise an approximation to the expectation of the utility function.") behaviour of the variance components in the classical twin models with respect to age using B-splines and P-splines.") (license license:gpl2+))) + +(define-public r-acfmperiod + (package + (name "r-acfmperiod") + (version "1.0.0") + (source + (origin + (method url-fetch) + (uri (cran-uri "acfMPeriod" version)) + (sha256 + (base32 + "1yww8isfrbs2v9s94hx7p2imyszcgadwafdgpj438n2ik0q6p9d5")))) + (properties `((upstream-name . "acfMPeriod"))) + (build-system r-build-system) + (propagated-inputs + `(("r-mass" ,r-mass))) + (home-page "https://cran.r-project.org/web/packages/acfMPeriod/") + (synopsis "Estimation of the ACF from the M-periodogram") + (description + "This package support non-robust and robust computations of the sample +autocovariance (ACOVF) and sample autocorrelation functions (ACF) of +univariate and multivariate processes. The methodology consists in reversing +the diagonalization procedure involving the periodogram or the +cross-periodogram and the Fourier transform vectors, and, thus, obtaining the +ACOVF or the ACF as discussed in Fuller (1995) +@url{doi:10.1002/9780470316917}. The robust version is obtained by fitting +robust M-regressors to obtain the M-periodogram or M-cross-periodogram as +discussed in Reisen et al. (2017) @url{doi:10.1016/j.jspi.2017.02.008}.") + (license license:gpl2+))) |