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(define-module (vkraus packages manuscript))

(use-modules
 (guix packages)
 ((guix licenses) #:prefix license:)
 (guix download)
 (guix git-download)
 (guix build-system gnu)
 (guix build-system r)
 (guix licenses)
 (gnu packages)
 (gnu packages commencement)
 (gnu packages base)
 (gnu packages autotools)
 (gnu packages emacs)
 (gnu packages emacs-xyz)
 (gnu packages tex)
 (gnu packages statistics)
 (gnu packages python-xyz)
 (gnu packages compression)
 (gnu packages imagemagick)
 (gnu packages xml)
 (gnu packages cran)
 (gnu packages inkscape)
 (gnu packages graphics)
 (gnu packages ghostscript)
 (vkraus packages h4sp))

(define r-lamw
  (package
   (name "r-lamw")
   (version "2.0.0")
   (source
    (origin
     (method url-fetch)
     (uri (cran-uri "lamW" version))
     (sha256
      (base32
       "03aisn5qmhia61glm1lrcjxj73qp4qfhn6nc964gpnl5h9nwzhnw"))))
   (properties `((upstream-name . "lamW")))
   (build-system r-build-system)
   (propagated-inputs
    `(("r-rcpp" ,r-rcpp)
      ("r-rcppparallel" ,r-rcppparallel)))
   (home-page "https://github.com/aadler/lamW")
   (synopsis "Lambert-W Function")
   (description
    "Implements both real-valued branches of the Lambert-W function (Corless et al, 1996) <doi:10.1007/BF02124750> without the need for installing the entire GSL.")
   (license bsd-2)))

(define r-texreg
  (package
   (name "r-texreg")
   (version "1.37.5")
   (source
    (origin
     (method url-fetch)
     (uri (cran-uri "texreg" version))
     (sha256
      (base32
       "0cb3kvxfi9k9g958fkb73cgqdxx3h9bz2cnaakic4wgrkv27mk2c"))))
   (properties `((upstream-name . "texreg")))
   (build-system r-build-system)
   (inputs
    `())
   (propagated-inputs `(("r-httr" ,r-httr)))
   (home-page "http://github.com/leifeld/texreg/")
   (synopsis
    "Conversion of R Regression Output to LaTeX or HTML Tables")
   (description
    "Converts coefficients, standard errors, significance stars, and goodness-of-fit statistics of statistical models into LaTeX tables or HTML tables/MS Word documents or to nicely formatted screen output for the R console for easy model comparison.  A list of several models can be combined in a single table.  The output is highly customizable.  New model types can be easily implemented. (If the Zelig package, which this package enhances, cannot be found on CRAN, you can find it at <https://github.com/IQSS/Zelig>.)")
   (license gpl3)))


(define r-greybox
  (package
   (name "r-greybox")
   (version "0.6.8")
   (source
    (origin
     (method url-fetch)
     (uri (cran-uri "greybox" version))
     (sha256
      (base32
       "1fz1qrj245hrf35bvfd7k56gz668dc644l2nlhdvhkjcqyhwy4k7"))))
   (properties `((upstream-name . "greybox")))
   (build-system r-build-system)
   (propagated-inputs
    `(("r-forecast" ,r-forecast)
      ("r-lamw" ,r-lamw)
      ("r-matrix" ,r-matrix)
      ("r-nloptr" ,r-nloptr)
      ("r-pracma" ,r-pracma)
      ("r-rcpp" ,r-rcpp)
      ("r-statmod" ,r-statmod)
      ("r-texreg" ,r-texreg)
      ("r-zoo" ,r-zoo)))
   (native-inputs `(("r-knitr" ,r-knitr)))
   (home-page
    "https://github.com/config-i1/greybox")
   (synopsis
    "Toolbox for Model Building and Forecasting")
   (description
    "Implements functions and instruments for regression model building and its application to forecasting.  The main scope of the package is in variables selection and models specification for cases of time series data.  This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more.  Models developed in the package are tailored specifically for forecasting purposes.  So as a results there are several methods that allow producing forecasts from these models and visualising them.")
   (license gpl2+)))

(define r-smooth
  (package
   (name "r-smooth")
   (version "3.1.0")
   (source
    (origin
     (method url-fetch)
     (uri (cran-uri "smooth" version))
     (sha256
      (base32
       "0d0rkn7q7n9h9mg9lvgfw7af7f59jfmkm4cqk34wzi4fiypmgscb"))))
   (properties `((upstream-name . "smooth")))
   (build-system r-build-system)
   (propagated-inputs
    `(("r-greybox" ,r-greybox)
      ("r-mass" ,r-mass)
      ("r-nloptr" ,r-nloptr)
      ("r-pracma" ,r-pracma)
      ("r-rcpp" ,r-rcpp)
      ("r-rcpparmadillo" ,r-rcpparmadillo)
      ("r-statmod" ,r-statmod)
      ("r-zoo" ,r-zoo)))
   (native-inputs `(("r-knitr" ,r-knitr)))
   (home-page "https://github.com/config-i1/smooth")
   (synopsis "Forecasting Using State Space Models")
   (description
    "This package provides functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting.  The package includes Exponential Smoothing (Hyndman et al., 2008, <doi: 10.1007/978-3-540-71918-2>), SARIMA (Svetunkov & Boylan, 2019 <doi: 10.1080/00207543.2019.1600764>), Complex Exponential Smoothing (Svetunkov & Kourentzes, 2018, <doi: 10.13140/RG.2.2.24986.29123>), Simple Moving Average (Svetunkov & Petropoulos, 2018 <doi: 10.1080/00207543.2017.1380326>), Vector Exponential Smoothing (de Silva et al., 2010, <doi: 10.1177/1471082X0901000401>) in state space forms, several simulation functions and intermittent demand state space models.  It also allows dealing with intermittent demand based on the iETS framework (Svetunkov & Boylan, 2017, <doi: 10.13140/RG.2.2.35897.06242>).")
   (license gpl2+)))

(define r-mapa
  (package
   (name "r-mapa")
   (version "2.0.4")
   (source
    (origin
     (method url-fetch)
     (uri (cran-uri "MAPA" version))
     (sha256
      (base32
       "02s223s58k2jk49m0xlz3q9m3nip3h4dl4v58j18z2vgi54dwnjr"))))
   (properties `((upstream-name . "MAPA")))
   (build-system r-build-system)
   (propagated-inputs
    `(("r-forecast" ,r-forecast)
      ("r-rcolorbrewer" ,r-rcolorbrewer)
      ("r-smooth" ,r-smooth)))
   (home-page
    "http://kourentzes.com/forecasting/2014/04/19/multiple-aggregation-prediction-algorithm-mapa/")
   (synopsis
    "Multiple Aggregation Prediction Algorithm")
   (description
    "This package provides functions and wrappers for using the Multiple Aggregation Prediction Algorithm (MAPA) for time series forecasting.  MAPA models and forecasts time series at multiple temporal aggregation levels, thus strengthening and attenuating the various time series components for better holistic estimation of its structure.  For details see Kourentzes et al. (2014) <doi:10.1016/j.ijforecast.2013.09.006>.")
   (license gpl2+)))

(define-public r-tsutils
  (package
   (name "r-tsutils")
   (version "0.9.2")
   (source
    (origin
     (method url-fetch)
     (uri (cran-uri "tsutils" version))
     (sha256
      (base32
       "0gp8f0a9dn3h4lv38xiw04j832igwhfralzc5vd74r952x7b6hbx"))))
   (properties `((upstream-name . "tsutils")))
   (build-system r-build-system)
   (propagated-inputs
    `(("r-forecast" ,r-forecast)
      ("r-mapa" ,r-mapa)
      ("r-plotrix" ,r-plotrix)
      ("r-rcolorbrewer" ,r-rcolorbrewer)))
   (home-page "https://github.com/trnnick/tsutils/")
   (synopsis
    "Time Series Exploration, Modelling and Forecasting")
   (description
    "Includes: (i) tests and visualisations that can help the modeller explore time series components and perform decomposition; (ii) modelling shortcuts, such as functions to construct lagmatrices and seasonal dummy variables of various forms; (iii) an implementation of the Theta method; (iv) tools to facilitate the design of the forecasting process, such as ABC-XYZ analyses; and (v) \"quality of life\" functions, such as treating time series for trailing and leading values.")
   (license gpl3)))

(define-public r-akima
  (package
   (name "r-akima")
   (version "0.6-2.1")
   (source
    (origin
     (method url-fetch)
     (uri (cran-uri "akima" version))
     (sha256
      (base32
       "086q4ip6j226p8z5iqzfg551i15l5c0rnf4y4zavmpmqvwd2szz2"))))
   (properties `((upstream-name . "akima")))
   (build-system r-build-system)
   (propagated-inputs `(("r-sp" ,r-sp)))
   (native-inputs `(("gfortran-toolchain" ,gfortran-toolchain)))
   (home-page
    "https://cran.r-project.org/web/packages/akima")
   (synopsis
    "Interpolation of Irregularly and Regularly Spaced Data")
   (description
    "Several cubic spline interpolation methods of H.  Akima for irregular and regular gridded data are available through this package, both for the bivariate case (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697).  Linear interpolation of irregular gridded data is also covered by reusing D.  J.  Renkas triangulation code which is part of Akimas Fortran code.  A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids.")
   (license #f)))

(define-public manuscript
  (package
   (name "manuscript")
   (version "1.1.0")
   (source (origin
	    (method git-fetch)
	    (uri (git-reference
		  (url "https://labo.planete-kraus.eu/manuscript.git")
		  (commit "abcc35e552cbd2ec455267704e082f45b28a780e")))
	    (sha256
	     (base32
	      "10f6cc3p59x5v4q518nvqxzig786wfrl0ifbvjbsgll8l3abxx0j"))))
   (build-system gnu-build-system)
   (arguments
    `(#:phases
       (modify-phases
	%standard-phases
	(add-after
	 'unpack 'set-XML_CATALOG_FILES
	 (lambda* (#:key inputs #:allow-other-keys)
	   (setenv "XML_CATALOG_FILES"
		   (string-append
		    (assoc-ref inputs "h4sp")
		    "/share/h4sp/catalog"))
	   #t)))))
   (native-inputs
    `(("texlive" ,texlive)
      ("inkscape" ,inkscape-1.1)
      ("r" ,r)
      ("r-ggplot2" ,r-ggplot2)
      ("r-magrittr" ,r-magrittr)
      ("r-dplyr" ,r-dplyr)
      ("r-tibble" ,r-tibble)
      ("r-gridextra" ,r-gridextra)
      ("r-tidyr" ,r-tidyr)
      ("r-akima" ,r-akima)
      ("r-reshape2" ,r-reshape2)
      ("r-tsutils" ,r-tsutils)
      ("autoconf" ,autoconf)
      ("autoconf-archive" ,autoconf-archive)
      ("automake" ,automake)
      ("libxslt" ,libxslt)
      ("h4sp" ,h4sp)))
   (inputs `())
   (propagated-inputs `())
   (synopsis "")
   (description "")
   (home-page "")
   (license "None")))