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| author | Ricardo Wurmus <rekado@elephly.net> | 2019-12-14 10:07:26 +0100 |
|---|---|---|
| committer | Ricardo Wurmus <rekado@elephly.net> | 2019-12-14 13:35:55 +0100 |
| commit | 70c0dbe73fa099cd7bebccb3bffba3dfe3c3137b (patch) | |
| tree | 9d8404879204eb1f0c30cc3f710bc31892abd0b0 /gnu | |
| parent | 6f0a5ab09819d1237d7434f1565db3016d785c8a (diff) | |
| download | patches-70c0dbe73fa099cd7bebccb3bffba3dfe3c3137b.tar patches-70c0dbe73fa099cd7bebccb3bffba3dfe3c3137b.tar.gz | |
gnu: Add r-gdina.
* gnu/packages/cran.scm (r-gdina): New variable.
Diffstat (limited to 'gnu')
| -rw-r--r-- | gnu/packages/cran.scm | 40 |
1 files changed, 40 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 22e994059b..cb68994565 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -17798,3 +17798,43 @@ Algorithm; it is used for optimizing smooth nonlinear objective functions with constraints. Linear or nonlinear equality and inequality constraints are allowed.") (license license:gpl2+))) + +(define-public r-gdina + (package + (name "r-gdina") + (version "2.7.3") + (source + (origin + (method url-fetch) + (uri (cran-uri "GDINA" version)) + (sha256 + (base32 + "0875xfbm36gqzr0116xzlbm8rlff85rybr4s4hjzfflfvjdhgvfx")))) + (properties `((upstream-name . "GDINA"))) + (build-system r-build-system) + (propagated-inputs + `(("r-alabama" ,r-alabama) + ("r-ggplot2" ,r-ggplot2) + ("r-mass" ,r-mass) + ("r-nloptr" ,r-nloptr) + ("r-numderiv" ,r-numderiv) + ("r-rcpp" ,r-rcpp) + ("r-rcpparmadillo" ,r-rcpparmadillo) + ("r-rsolnp" ,r-rsolnp) + ("r-shiny" ,r-shiny) + ("r-shinydashboard" ,r-shinydashboard))) + (home-page "https://github.com/Wenchao-Ma/GDINA") + (synopsis "Generalized DINA model framework") + (description + "This package provides a set of psychometric tools for cognitive +diagnosis modeling based on the generalized deterministic inputs, noisy and +gate (G-DINA) model by de la Torre (2011) @url{doi:10.1007/s11336-011-9207-7} +and its extensions, including the sequential G-DINA model by Ma and de la +Torre (2016) @url{doi:10.1111/bmsp.12070} for polytomous responses, and the +polytomous G-DINA model by Chen and de la Torre +@url{doi:10.1177/0146621613479818} for polytomous attributes. Joint attribute +distribution can be independent, saturated, higher-order, loglinear smoothed +or structured. Q-matrix validation, item and model fit statistics, model +comparison at test and item level and differential item functioning can also +be conducted. A graphical user interface is also provided.") + (license license:gpl3))) |